A method for extracting and correlating design conflict features of historical block reconstruction

Abstract

The application provides a design conflict feature extraction and correlation discrimination method for historical block reconstruction, and relates to the field of data processing. In the method, a target historical block spatial object set is obtained and a block identifier is established, object identifiers are generated for spatial objects and object attribute sets are constructed, and on this basis, object state clusters are formed; the protection list, style guide, control regulation clause, mandatory specification, approval history and reconnaissance record are semantically disassembled to form a constraint statement set and a trigger relationship mapping is established; a local context set composed of object subsets, state subsets, statement subsets and spatial relationship subsets is constructed; the reconstruction design scheme is analyzed to generate a change identifier and update the context state and statement; the change context is subjected to satisfiability judgment, and when it is not satisfied, the design conflict feature is extracted and a conflict correlation hypergraph is constructed to realize conflict discrimination. The implementation of the technical scheme facilitates the stable extraction and correlation discrimination of design conflict features.

Description

Technical Field

[0001] This application relates to the technical field of data processing, specifically to a method for extracting and identifying design conflict features in the renovation of historical districts. Background Technology

[0002] Historic districts are important spatial carriers formed during the historical evolution of a city. Their architectural forms, street patterns, spatial scale, and stylistic elements collectively constitute an environment of historical value. With the continuous expansion and renewal of cities, some historic districts gradually overlap and permeate with the surrounding modern urban spaces, forming transitional areas where historical, modern, and contemporary buildings coexist in terms of spatial structure. These transitional areas exhibit distinct mixed characteristics in terms of spatial form, function, and stylistic features. They include both objects subject to historical preservation and those constructed according to modern planning systems, thus creating a degree of ambiguity and gradual change in the actual controllable scope of historic districts.

[0003] In the design process of historic district renovation, design schemes typically need to simultaneously meet requirements for historical preservation, urban planning control, and relevant technical specifications. Existing design conflict identification technologies usually rely on clearly defined historic district boundaries and a single rule system. This involves matching the design object with a pre-defined control area and determining the compliance of design elements based on the corresponding rule system. However, in historic districts with ambiguous boundaries, different rule systems often have different applicable scopes and control requirements for the same spatial object. For example, historic preservation guidelines may emphasize the historical consistency of building height, materials, and interface continuity, while urban planning control clauses may focus more on floor area ratio, functional layout, or traffic organization. When the same spatial object is located in the transition zone between historic preservation control and modern planning control, different rule systems may impose different constraints on the same design element. In this case, traditional design conflict identification methods based on fixed boundaries and single rule matching are insufficient to accurately express the rule applicability relationships in ambiguous boundary areas. When the design scheme involves this type of area, the system may produce different conflict judgment results under different rule systems. In some cases, the same design element may be judged as compliant under one rule system but as conflicting under another rule system, thus affecting the consistency and reliability of the design conflict identification results.

[0004] Therefore, how to uniformly express the applicability of different rule systems in the case of areas with ambiguous boundaries of historical districts, and how to achieve stable extraction and correlation identification of design conflict characteristics, has become a technical problem that urgently needs to be solved in the field of auxiliary decision-making for the renovation design of historical districts. Summary of the Invention

[0005] This application provides a method for extracting and identifying design conflict features in the renovation of historical blocks, which facilitates the stable extraction and identification of design conflict features even in areas with ambiguous boundaries of historical blocks.

[0006] The first aspect of this application provides a method for extracting and identifying design conflict features in the renovation of historical blocks. The method includes: acquiring a set of spatial objects of a target historical block and establishing a block identifier; generating an object identifier for each spatial object in the set and solidifying an object attribute set, the object attribute set including spatial geometric attributes, chronological hierarchy attributes, landscape element attributes, ownership and use attributes, regulatory applicability attributes, and evidence index attributes; constructing an object state cluster around the object identifier and the object attribute set, the object state cluster including spatial geometric state, chronological hierarchy state, landscape element state, ownership and use state, and regulatory applicability state; performing semantic decomposition on the protection list, landscape guidelines, control regulations, mandatory regulations, approval history, and site survey records of the target historical block to form a set of constraint statements, and establishing a trigger relationship between the set of constraint statements and the object state cluster. The system maps the target historical district into a set of local scenarios and scenario identifiers based on the street identifiers. The set of local scenarios consists of a subset of objects, a subset of states, a subset of statements, and a subset of spatial relationships. The subset of statements is formed by the constraint statements activated under the conditions of the state subset and the spatial relationship subset, as mapped by the triggering relationship. The renovation design scheme of the target historical district is parsed into a change identifier, and the change identifier is applied to the scenario identifier to update the state subset and recalculate the statement subset to obtain the changed scenario identifier. Satisfaction determination is performed on the changed scenario identifier. When the determination result is determined to be unsatisfying, the corresponding design conflict features are extracted and the set of statements that the target cannot be simultaneously established and the target changed subset are output. A conflict association hypergraph is constructed based on the set of statements that the target cannot be simultaneously established and the target changed subset to complete the extraction and association discrimination of design conflict features for the renovation of the historical district.

[0007] A second aspect of this application provides a device for extracting and identifying design conflict features in the renovation of historical blocks. The device includes an acquisition module and a processing module. The acquisition module acquires a set of spatial objects of a target historical block and establishes a block identifier. It generates an object identifier for each spatial object in the set and solidifies a set of object attributes, including spatial geometric attributes, chronological hierarchy attributes, landscape element attributes, ownership and usage attributes, regulatory applicability attributes, and evidence index attributes. The processing module constructs an object state cluster around the object identifier and the object attribute set. The object state cluster includes spatial geometric state, chronological hierarchy state, landscape element state, ownership and usage state, and regulatory applicability state. The processing module further performs semantic decomposition on the protection list, landscape guidelines, regulatory clauses, mandatory regulations, approval history, and site survey records of the target historical block to form a set of constraint statements, and associates the set of constraint statements with the object state cluster. The processing module establishes a trigger relationship mapping; it is further configured to construct a local context set and a context identifier based on the street identifier. The local context set consists of an object subset, a state subset, a statement subset, and a spatial relationship subset. The statement subset is formed by constraint statements activated under the conditions of the state subset and the spatial relationship subset by the trigger relationship mapping. The processing module is further configured to parse the renovation design scheme of the target historical street into a change identifier and apply the change identifier to the context identifier to update the state subset and recalculate the statement subset to obtain the change context identifier. The processing module is further configured to perform a satisfiability determination on the change context identifier. When the determination result is determined to be unsatisfiable, it extracts the corresponding design conflict features and outputs the target non-simultaneous statement set and the target change subset. It then constructs a conflict association hypergraph based on the target non-simultaneous statement set and the target change subset to complete the extraction and association discrimination of design conflict features for the renovation of the historical street.

[0008] A third aspect of this application provides an electronic device including a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, and both the user interface and the network interface are used to communicate with other devices. The processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method described above.

[0009] A fourth aspect of this application provides a non-transitory computer-readable storage medium storing instructions that, when executed, perform the method described above.

[0010] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages:

[0011] By constructing a spatial object set and object identification system, spatial objects in historical districts are expressed in a unified and structured manner. Object attribute sets and object state clusters are used to describe the multiple possible states of spatial objects under different attribute conditions, thereby improving the ability to express complex spatial information in historical districts. Based on this, various planning and protection rules are semantically decomposed and a set of constraint statements is established. Through trigger relationship mapping, precise matching between rule conditions and object states is achieved, enabling collaborative judgment across different rule systems within a unified framework. Furthermore, by constructing a set of local scenarios and introducing spatial relationship constraints, dynamic state updates and rule recalculations are performed on design scheme changes, thereby achieving early identification of design conflicts. Simultaneously, by using satisfiability judgment and conflict association hypergraph analysis, the sources of conflict and their relationships are analyzed, thereby improving the accuracy, stability, and interpretability of identifying design conflicts in historical district renovation designs. Therefore, it is convenient to achieve stable extraction and association discrimination of design conflict features even in areas with ambiguous boundaries in historical districts. Attached Figure Description

[0012] Figure 1 A flowchart illustrating a method for extracting and identifying design conflict features in the renovation of historical districts, provided in an embodiment of this application;

[0013] Figure 2 A schematic diagram of a module for extracting and identifying design conflict features in the renovation of historical districts, provided in an embodiment of this application;

[0014] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0015] Explanation of reference numerals in the attached figures: 21. Acquisition module; 22. Processing module; 31. Processor; 32. Communication bus; 33. User interface; 34. Network interface; 35. Memory. Detailed Implementation

[0016] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0017] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0018] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0019] To address the aforementioned technical problems, this application provides a method for extracting and identifying design conflict features in the renovation of historical districts, referring to... Figure 1 , Figure 1 This is a flowchart illustrating a method for extracting and identifying design conflict features in the renovation of historical districts, provided in an embodiment of this application. The method is applied to a server and includes steps S110 to S160, as follows:

[0020] S110. Obtain the spatial object set of the target historical block and establish the block identifier. Generate an object identifier for each spatial object in the spatial object set and solidify the object attribute set. The object attribute set includes spatial geometric attributes, age hierarchy attributes, landscape element attributes, ownership and use attributes, standard application attributes, and evidence index attributes.

[0021] Specifically, a server is a computing device that provides computing resources, data storage capabilities, and network service capabilities. Its core function is to continuously receive requests from terminal devices or other systems in a network environment, perform computational processing, data retrieval, or service responses to these requests, and then return the processing results to the client or other systems. When constructing a spatial object set under the constraints of street block identifiers, the management boundaries and version information of the street block identifiers are first determined, and the street block identifiers are bound to a unified evidence index directory. This ensures that any subsequent spatial object can be traced back to a verifiable location index of the corresponding surveying results, point cloud results, street view images, aerial photographs, historical archives, and reconnaissance records. Subsequently, the spatial entities within the street block area are normalized by object type. Building objects are defined as entities with closable outlines and height attributes; interface objects are defined as facade continuous segments formed along street or plot boundaries; street objects are defined as passageway entities with centerlines and cross-sectional zones; plot objects are defined as land use unit entities with legal or existing boundaries; and node objects are defined as streets. Key spatial entities that intersect, turn, or cluster functions are defined as underground impact objects, which are underground facilities or protected areas that constrain surface modifications. For each spatial object, an object identifier is generated, and a unique correspondence is established between the object identifier and the geometric carrier. The geometric carrier is used to carry the spatial expression of the spatial object. Building objects correspond to the building outline polygon and height range, interface objects correspond to the interface centerline and normal surface, street and alley objects correspond to the street and alley centerline and cross-sectional zone, plot objects correspond to the plot boundary polygon, node objects correspond to the node location and view sector, and underground impact objects correspond to the underground impact range volume. This ensures that once the object identifier is determined, it can stably point to the unique geometric carrier and support subsequent attribute solidification and rule triggering calculations.

[0022] When constructing the initial object attribute set based on object identifiers, an object attribute record is first established for each object identifier and a field system is loaded. The field system includes at least spatial geometric attributes, chronological attributes, landscape element attributes, ownership and usage attributes, standard application attributes, and evidence index attributes. Spatial geometric attributes are used to record attributes directly related to or deducible from geometric carriers, such as building height range, number of floors range, setback relationship, opening density description, interface continuous length description, street width variation description, node accessibility description, and underground influence range description. Chronological attributes are used to record historical time periods, repair time periods, and renovation years. The system is divided into several parts: the generation segment and the age determination criteria; the style element attribute is used to record the material genealogy, color genealogy, component type genealogy, facade rhythm type and roof form type; the ownership and use attribute is used to record the ownership unit identifier, use type, operating period characteristics and public level; the standard application attribute is used to record the clause system identifier, applicable object domain mark, applicable condition trigger tag and exception condition trigger tag; the evidence index attribute is used to establish a verifiable location index for the value of each field and its source evidence fragment, and record the evidence consistency summary, so that the initial object attribute set is not only a set of values, but also a set of object attribute records with evidence chain.

[0023] When performing cross-source alignment and deduplication on the initial object attribute set, cross-source alignment prioritizes resolving inconsistencies in coordinate references, acquisition times, and representation scales among different data sources. This ensures that descriptions of the same geometric entity from different sources fall within the same spatial framework. Coordinate datum unification maps survey coordinates, point cloud coordinates, and drawing coordinates to a unified coordinate reference. Coordinate transformation parameters are estimated by selecting control point pairs or feature-corresponding point pairs, and all geometric entities are uniformly transformed to complete spatial alignment. The expression for this coordinate transformation is:

[0024] ;

[0025] in, Represents the coordinate vector of the point before transformation. This represents the transformed point coordinate vector. This represents the rotation matrix, obtained by fitting control point pairs. The above formula represents the translation vector, which is obtained by fitting control point pairs. It is determined by minimizing the transformation residuals of the control point pairs. and This achieves a unified coordinate reference; unified time stamps are used to bind data from different collection batches to a unified time coverage interval and mark the current valid version, avoiding mixing historical and current states in the same object attribute record; unified scale is used to consistently express geometric carriers from different precision sources according to the minimum usable precision requirements of the object type, for example, extracting the outline of high-precision point cloud boundaries and low-precision drawing boundaries under the same resolution rules and maintaining topological consistency; deduplication is used to ensure that each spatial object corresponds to only one unique object identifier, where geometric overlap discrimination is used to compare the degree of spatial overlap of geometric carriers of the same type and determine whether they are the same spatial object, and its geometric overlap discrimination expression is:

[0026] ;

[0027] in, Represents the geometric region of a spatial object. Represents the geometric region of another spatial object. This indicates the area or volume of the region where the two intersect. This indicates the area or volume of the region where the two are joined. The closer to 1, the higher the degree of overlap and the more likely they are the same spatial object; the name alias merging discrimination is used to merge different names for the same object in different materials into the same object identifier, avoiding duplicate objects caused by naming differences; the evidence index consistency discrimination is used to compare whether the evidence index attributes of two sets of object attribute records point to the same or highly overlapping verifiable location index, so as to further confirm whether they are the same spatial object when they are geometrically similar and have similar names, thereby achieving the uniqueness and stability of object identifiers.

[0028] When performing consistency solidification processing on the initial object attribute set, firstly, under the street identifier constraint, a field completeness check is performed on each object attribute record to confirm whether the required fields of the object type dictionary are complete, and an evidence gap marker is generated for missing fields to avoid misinterpreting missing fields as non-compliance when subsequent rules are triggered; then, a field conflict check is performed to identify contradictory values ​​of the same field from different evidence index attributes, and the set of contradictory values ​​and the corresponding evidence index attributes are written into the conflict marker for subsequent review; finally, an evidence threshold check is performed to determine whether the value of a certain field reaches the solidification threshold, thus solidifying the data. The threshold is constrained by the credibility of the evidence source, the consistency summary of the evidence, and the time coverage interval. When the value reaches the solidification threshold, the field is written into the deterministic area. When the value does not reach the solidification threshold but there are still multiple reasonable candidate values, the field is written into the uncertain area and bound to the candidate value set and the evidence index attribute. Finally, an object attribute set corresponding to the street identifier is formed, so that the object attribute set has both a deterministic area for stable triggering and judgment, and an uncertain area for explicitly expressing the coexistence of multiple interpretations in the ambiguous boundary area. This provides a consistent, traceable and verifiable data foundation for the subsequent construction of object state clusters and the mapping of constraint statement triggering relationships.

[0029] S120. Construct an object state cluster around the object identifier and object attribute set. The object state cluster includes spatial geometric state, chronological level state, landscape element state, ownership and usage state, and standard application state.

[0030] Specifically, when establishing a state generation context for each object identifier under the constraint of street identifiers, the object attribute record corresponding to the object identifier is first read, and the definite and uncertain areas in the object attribute record are separated and saved. The definite area field serves as the stable anchor point for state generation, and the uncertain area field serves as the variable dimension for state generation. At the same time, the evidence index attribute in the object attribute record is incorporated into the state generation context to retain the verifiable location index and the evidence consistency summary. Then, based on the spatial object set and spatial relationship subset, the set of adjacent object identifiers that have spatial relationships with the object identifier is determined. The set of adjacent object identifiers is used to express the set of object identifiers that are coupled with the current object identifier in terms of adjacency, occlusion, line-of-sight, or passage relationships. This allows the state generation context to include not only the source of the object's attributes and the source of uncertainty, but also the neighborhood constraint information necessary for subsequent spatial relationship consistency screening. The state generation context refers to the minimum information closure required to generate candidate states; the object attribute record refers to the structured field set with the object identifier as the primary key; the deterministic zone refers to the field set that meets the evidence threshold and whose values ​​can be directly fixed; the uncertain zone refers to the field set that does not meet the evidence threshold but has a set of candidate values; the evidence index attribute refers to the attribute field that binds the field value to the verifiable location index and consistency summary of the source evidence fragment; and the adjacent object identifier set refers to the set of object identifiers that have a spatial relationship with the current object identifier and need to jointly satisfy spatial constraints.

[0031] When enumerating candidate states based on the state generation context to form an initial object state cluster, the object type dictionary is first loaded and the object type of the current object identifier is locked, ensuring that the candidate state enumeration conforms to the field definitions and legal value ranges of that object type. Then, the field dependency graph is loaded and aligned with the field system of the object attribute records. The field dependency graph expresses the compatibility and mutual exclusion relationships between fields, thus avoiding the concatenation of incompatible field values ​​into the same candidate state during combination and expansion. Subsequently, the field values ​​in the definite region of the object attribute records are used as the fixed part, and the set of candidate values ​​in the indefinite region of the object attribute records are used as the variable part for combination and expansion. The self-consistency of the candidate combination is verified using the field dependency graph during each expansion, resulting in multiple candidate states that are aggregated into the initial object state cluster. Each candidate state fully encompasses the spatial geometric state, the chronological level state, and the landscape element state. The categories are: ownership and usage status, and standard application status. Spatial geometric status corresponds to the state-based expression of spatial geometric attributes and is consistent with the geometric carrier. Chronological level status corresponds to the state-based expression of chronological level attributes under candidate values. Landscape element status corresponds to the state-based expression of landscape element attributes under candidate values. Ownership and usage status corresponds to the state-based expression of ownership and usage attributes under candidate values. Standard application status corresponds to the state-based expression of standard application attributes under candidate values. The object type dictionary refers to a rule dictionary that uniformly defines object types and their field sets. The field dependency graph refers to a structured constraint graph describing the dependencies and mutual exclusions between fields. Candidate state enumeration refers to the process of generating multiple feasible field combinations on the candidate value set in the uncertain region. The initial object state cluster refers to a set of candidate states composed of multiple candidate states that have not yet undergone spatial relationship consistency filtering and standard application consistency convergence processing.

[0032] When generating evidence fingerprints and credibility levels for each candidate state, the evidence index attribute set corresponding to each field value is first extracted from the candidate state. This set is then structurally aggregated according to source type, time coverage interval, and consistency summary to form the evidence fingerprint. This ensures that the evidence fingerprint simultaneously includes the mapping relationship from fields to evidence, the distribution of evidence source types, the distribution of evidence time coverage intervals, and the aggregated result of evidence consistency summaries. The credibility level is used for comparable ranking of candidate states. The credibility level is jointly determined by the evidence consistency summary, evidence time coverage interval, and evidence source credibility label. To ensure the verifiability of the credibility level, it is decomposed into a combination of consistency score, time coverage score, and source credibility score. The same combination rule is used for all candidate states within the same object identifier range, thereby avoiding inconsistencies in scoring criteria between different candidate states. The expression for the credibility level is:

[0033] ;

[0034] in, This indicates the trust level value, which ranges from 0 to 1. , , Represents the weight coefficients and satisfies , This represents the consistency score, ranging from 0 to 1. It is determined based on the evidence consistency summary, with higher consistency scores resulting in larger values. This represents the timeliness coverage score, ranging from 0 to 1. It is determined by the degree of overlap between the evidence's time coverage interval and the current effective time window of the street signage, with a higher value indicating greater overlap. The source credibility score ranges from 0 to 1 and is obtained by mapping the source credibility label. The higher the source credibility, the larger the value. Among them, the evidence fingerprint refers to the set of structured features that compress the evidence support structure of the candidate state; the source type refers to evidence categories such as surveying results, point cloud results, street view images, aerial photography, historical archives, approval documents and survey records; the time coverage interval refers to the time range of the evidence's validity for the object's state; the consistency summary refers to the aggregated description of whether the values ​​of the same field of multiple pieces of evidence are consistent; and the evidence source credibility label refers to the graded marking of the reliability of the evidence source.

[0035] When performing spatial relationship consistency screening and specification application consistency convergence processing on the initial object state cluster, and combining evidence fingerprints and trust levels to generate object state clusters, the spatial relationship consistency screening is performed within the set of adjacent object identifiers. Each candidate state of the current object identifier is paired with the corresponding candidate state of the object identifier in the set of adjacent object identifiers for verification. In the pairing verification, the spatial relationship records corresponding to the adjacency, occlusion, line-of-sight, and passage relationships defined in the spatial relationship subset are read. It is determined whether the current candidate state has at least one feasible pairing under any key spatial constraint. If no feasible pairing exists, the candidate state is marked as an unusable candidate state and removed or downgraded from the usable set of the object state cluster. To make the spatial relationship consistency screening process verifiable, a spatial consistency index can be used to normalize the pairing verification results. The expression for the spatial consistency index is:

[0036] ;

[0037] in, This indicates the value of the spatial consistency index, which ranges from 0 to 1. Indicates the number of spatial relation constraints involved in the test. Indicates the candidate state of the current object identifier. This indicates the candidate state of a certain adjacent object identifier. Indicates the first The difference measurement function corresponding to each spatial relation constraint. Indicates the first The allowable threshold corresponding to each spatial relationship constraint This indicates an indicator function; it takes the value 1 if the condition within the parentheses is true, and 0 otherwise. The larger the value, the higher the proportion of spatial relationship constraints passed. The norm application consistency convergence processing is used to stabilize the norm application status in the candidate status. First, the norm application status is decomposed into clause system identifier, applicable object domain marker, applicable condition trigger label, and exception condition trigger label. Then, the evidence threshold is determined for the exception condition trigger label based on the evidence fingerprint. When the evidence index attribute corresponding to the exception condition trigger label does not reach the evidence threshold, the exception condition trigger label is marked as inactive and the credibility level or the effective weight of the spatial consistency index is reduced simultaneously, thereby avoiding arbitrary switching of the norm application status due to insufficient evidence. Finally, the candidate status that has passed the spatial relationship consistency screening process and completed the norm application consistency convergence processing is used as the available candidate status of the object status cluster. The evidence fingerprint, credibility level, and spatial consistency index of each available candidate status are written into the object status record. This allows the object status cluster to express the coexistence of multiple interpretations in the boundary ambiguity area and ensures that the spatial coupling constraints across object identifiers are explicitly satisfied and verifiable.

[0038] S130. Semantic decomposition of the protection list, style guidelines, control plan clauses, mandatory norms, approval history and site survey records of the target historical blocks is performed to form a set of constraint statements, and a trigger relationship mapping is established between the set of constraint statements and the object state cluster.

[0039] Specifically, when compiling and establishing a rule evidence catalog based on the protection list, landscape guidelines, control regulations, mandatory norms, approval history, and site survey records under the constraints of street identifiers, the convergence boundary of the rule data is first fixed under the street identifier. This ensures that the same street identifier is only linked to source materials whose applicable geographical scope covers the street and whose time coverage interval is interpretable. Each source material is then abstracted into a material identifier. The material identifier uniquely identifies a rule material and its version instance. The time coverage interval describes the time range within which the material can be considered valid or of reference value. The applicable geographical scope describes which administrative units, control zones, or landscape control areas the material is effective for. The issuing entity identifies the organization that formed or issued the rule material to support subsequent source credibility labeling. The verifiable location index establishes a one-to-one correspondence between the material identifier and the verifiable location of the original material. The verifiable location index includes at least the file path or archive number, page number or page range, paragraph location information, and attached figure number location information, thereby providing a stable back-pointing link for subsequent semantic decomposition, trigger relationship mapping, and conflict tracing.

[0040] When performing text normalization on each material identifier in the rule evidence catalog to form normalized text, materials of different carrier forms are first uniformly converted into parsable text structures. Scanned or photocopied documents are converted into paragraph text through text transcription, table clauses are converted into paragraph text through table cell expansion, drawing notes are converted into paragraph text through note extraction, and free text of approval opinions and site survey records are converted into paragraph text through sentence segmentation. Then, structural annotation is performed on the normalized text, so that clause numbers, clause levels, reference clause links, term definition paragraphs, exception clause paragraphs, and applicable condition paragraphs are explicitly marked and can be indexed and called. The paragraph sequence refers to the set of paragraphs arranged according to the internal logical order of the materials, and the paragraph index identifier refers to the unique positioning number of each paragraph in the paragraph sequence, which consists of at least the material identifier, page number positioning, and paragraph sequence number, thereby ensuring that any constraint statements generated subsequently can be traced back to the original context and retain the reference relationship and definition relationship between clauses.

[0041] When performing semantic decomposition based on standardized text to form a set of constraint statements and generate statement identifiers, the following steps are taken: Obligation expressions, prohibited expressions, permitted expressions, and exception expressions are first identified at the paragraph index identifier granularity. Expressions that can independently form adjudication units are extracted as constraint statements, ensuring that each statement identifier carries only one adjudication target to avoid ambiguity. The applicable object domain is used to limit the scope of object types and object attribute ranges for the constraint statement's effect. Its output format is consistent with the object type dictionary and can be directly mapped to the object identifier set. The triggering condition describes under what object state and spatial relationship conditions the constraint statement is activated. The triggering condition is structured as a combination of state field constraints and spatial relationship constraints. The exception condition describes the conditions that allow a change in the adjudication method when specific approval history, specific site inspection evidence, or specific evidence fingerprint thresholds are met. The adjudication strength distinguishes between hard adjudication statements that must be met and soft adjudication statements that allow pending decisions. The clause source points to the material identifier and paragraph index identifier. The evidence index attribute records the terminology definition paragraphs, reference clause links, and evidence pointing to the set of evidence supporting the interpretability of the statement, thus making the set of constraint statements a computable, traceable, and verifiable rule representation.

[0042] When performing terminology alignment and alias merging on a set of constraint statements, a terminology mapping table is first established, using the field system of the object type dictionary and object attribute set as the sole semantic benchmark, ensuring that the same concept is expressed using only the same terminology throughout the entire process. Terminology alignment maps object names, landscape element names, usage names, and spatial relationship names in constraint statements to object type names in the object type dictionary and field names in the object attribute set, and uniformly maps spatial relationship terms to adjacency, occlusion, line-of-sight, or passage relationships. Alias ​​merging handles aliases, abbreviations, or historical names of the same term appearing in different material identifiers, merging them into the same standard terminology and recording the merging basis. The merging basis is given by the definition section or context constraint pointed to by the paragraph index identifier, thereby reducing the drift of trigger conditions caused by lexical differences between rule materials and providing a consistent field entry and consistent relationship entry for trigger table construction.

[0043] When constructing the trigger table, a searchable trigger index structure is generated for each constraint statement using the statement identifier as the primary key, making the trigger table the computational interface between the set of constraint statements and the object state cluster. When mapping the applicable object domain to the set of object types, the applicable object domain of the statement identifier is decomposed into object type constraints and object attribute constraints. The object type constraints are used to select the target object type set from building objects, interface objects, street objects, plot objects, node objects, and underground influence objects, while the object attribute constraints are used to limit the range of fields that must be satisfied in the object attribute records. When mapping the trigger conditions to the set of state field constraints and the set of spatial relationship subset constraints, the set of state field constraints is used to constrain the object state cluster. The field values ​​or field ranges for spatial geometric state, chronological level state, landscape element state, ownership and use state, and normative application state are defined. The spatial relationship subset constraint set is used to constrain the relationship type, relationship direction, and effective relationship range within the spatial relationship subset. When mapping exception conditions to evidence fingerprint thresholds and approval history matching conditions, the evidence fingerprint threshold is used to constrain the consistency and coverage of evidence required for the exception condition to be established, and the approval history matching condition is used to constrain the matching relationship between the approval material identifier and the paragraph index identifier required for the exception condition to be established. The evidence fingerprint threshold is solidified into an executable threshold scoring function to avoid exception condition triggering relying solely on subjective judgment. The expression of its threshold scoring function is:

[0044] ;

[0045] in, This represents the evidence threshold score, ranging from 0 to 1. A higher value indicates that the evidence threshold required to trigger the exception condition is more readily met. Represents a logical function. , used to compress linear combinations to 0 to 1; Indicates the bias term; arrive The weighting coefficients are represented and fixed in the trigger table; their values ​​can be set empirically or fitted from historical review data. This represents the evidence consistency score, ranging from 0 to 1. It is generated based on the consistency summary in the evidence index attribute, and the higher the consistency, the larger the value. This represents the evidence coverage score, ranging from 0 to 1. It is generated based on the degree of overlap between the evidence time coverage interval and the current effective time window of the street signage, with a larger value for more sufficient overlap. This represents the credibility score of the evidence source, with a value ranging from 0 to 1. It is obtained by mapping the credibility label of the evidence source, and the higher the credibility of the source, the larger the value. The score represents the completeness of the evidence chain, ranging from 0 to 1. It is generated based on whether the chain between the term definition section and the cited clause is completely closed, and the more complete the closure, the higher the score. This represents the penalty for conflict of evidence, with a value ranging from 0 to 1. It is generated based on the proportion of mutually exclusive values ​​given by different pieces of evidence for the same field, and the more conflicts there are, the larger the value. This represents the time drift penalty, with a value ranging from 0 to 1. It is generated based on the degree of deviation between the center time of the evidence time coverage interval and the center time of the current effective time window, and the larger the deviation, the larger the value. This represents the score for supporting evidence in the approval process, ranging from 0 to 1. It is generated based on the degree of coverage of key elements of the exception conditions by the approval history material identifier and paragraph index identifier, with a higher value for more comprehensive coverage. This represents the score for evidence support during the site visit, ranging from 0 to 1. It is generated based on the degree of direct identification of the object and spatial relationship in the site visit record, with a higher value for more comprehensive identification. This represents the score of multi-source consistent cross-validation, with a value range from 0 to 1. It is generated based on the proportion of surveying results, point cloud results, street view images, aerial photography, and historical archives that are simultaneously supported in key fields, and the higher the proportion, the larger the value. This represents the verifiability score of the evidence index, ranging from 0 to 1. The score is determined by whether the verifiability index in the evidence index attribute is complete and usable, with higher values ​​indicating greater verifiability. Not lower than the threshold value for triggering table solidification At that time, it was considered that the fingerprint threshold was met, and the threshold value was... The value ranges from 0 to 1 and can be set according to the strength of the ruling and the risk level of the exception conditions.

[0046] When establishing a trigger relationship mapping between the set of constraint statements and the object state cluster based on the trigger table, firstly, under the street identifier constraint, the candidate states in the object state cluster of each object identifier are traversed, and the candidate set of statement identifiers that match the object type of the object identifier are filtered according to the object type set of the trigger table; then, state field constraint matching and spatial relation subset constraint matching are performed on each candidate set of statement identifiers, and the matching results are written to the trigger record to bind the object identifier, candidate state identifier, statement identifier, trigger condition hit summary, and clause source; to avoid instability in triggering in areas with ambiguous boundaries caused by hard matching alone, the state field constraint and spatial relation subset constraint are merged into a trigger matching score and compared with the trigger threshold, thereby improving robustness while maintaining verifiability. The expression for the trigger matching score is:

[0047] ;

[0048] in, This indicates the trigger matching score, with a value ranging from 0 to 1. The larger the value, the more likely it should be judged as an activation statement identifier. arrive Represents the weight coefficients and satisfies And solidify it in the trigger table; This represents the matching score of the status field, with a value ranging from 0 to 1. It is generated based on the degree to which the spatial geometric status, chronological level status, landscape element status, ownership and usage status, and standard application status of the candidate status satisfy the set of constraints of the status field. This represents the spatial relationship matching score, with a value ranging from 0 to 1. It is generated based on the degree to which the spatial relationship subset constraint set is satisfied by adjacency, occlusion, line-of-sight, and passage relationships. This represents the condition coverage score, with a value ranging from 0 to 1. It is generated based on the proportion of each sub-condition in the triggering condition that is hit, and the more fully the conditions are hit, the larger the value. This represents a mutual exclusion penalty, ranging from 0 to 1. It is generated based on the number of mutually exclusive propositions appearing between the candidate state and the statement identifier triggering condition, with a larger value indicating more mutual exclusions. Not lower than the trigger threshold fixed in the trigger table The statement identifier is determined to be an active statement identifier, triggering the threshold. The value ranges from 0 to 1 and can be set according to the strength of the ruling; for statements containing exception conditions, further approval history matching condition determination and evidence fingerprint threshold determination are performed. The approval history matching condition determination is completed by searching for the hit relationship between material identifiers and paragraph index identifiers, and the evidence fingerprint threshold determination is performed by calculating the evidence threshold score. and threshold value The comparison is complete only if the approval history matching conditions are met and Not less than Only when the exception condition is activated will the accessibility flag of the adjudication be updated according to the adjudication strength rule; finally, a trigger relationship mapping is formed with the object identifier and candidate state identifier as indexes and the activated statement identifier as content, so that the subsequent local context set construction can directly extract the statement subset under the condition of state subset and spatial relationship subset and maintain the verifiability and consistency of rule application.

[0049] S140. Construct a local context set and context identifier based on street identifiers. The local context set consists of an object subset, a state subset, a statement subset, and a spatial relation subset. The statement subset is formed by constraint statements that are activated under the conditions of the state subset and the spatial relation subset, which are triggered by relation mapping.

[0050] Specifically, when constructing contextual domain division rules and generating contextual domain identifiers under the constraints of street signage, the spatial object set and geometric carriers bound to the street signage are first read, and the contextual domain division rules are solidified under the street signage. This ensures that the contextual domain division rules rely only on three types of geometric components: the arc length segments of street objects, the view sectors of node objects, and the boundary zones of plot objects, thus guaranteeing verifiability and stable updates. The arc length segment refers to the line segment unit obtained by dividing the centerline of the street object according to the cumulative arc length, used to express the local continuous space along the street direction. The view sector refers to the visible fan-shaped area obtained by taking the node object position as the vertex, the orientation set as the fan-shaped boundary, and combining the occlusion relationship, used to express the visual control shadow at key nodes. The influence range; the boundary zone refers to the strip-shaped area generated around the boundary of the land parcel object at a fixed buffer distance, used to express the influence range of interface control and backtracking control near the land parcel boundary; under the superposition and coverage of the above three types of geometric components, a context domain identifier is generated for each overlapping unit, and an inclusion relationship index is established between the context domain identifier and the object identifier in the spatial object set. The inclusion relationship index refers to a searchable mapping table from context domain identifier to object identifier, used to directly locate the set of object identifiers covered by a certain context domain identifier in subsequent steps; when it is necessary to perform geometric generation on the view sector, the boundary points of the view sector can be determined by the node point position, sector radius and sector angle range, and its polar coordinate to planar coordinate expression is:

[0051] ;

[0052] in, Represents the coordinates of a point on the sector boundary. Represents the coordinates of the node object. This represents the sector radius and is determined by the influence radius rules of the node object. The above formula represents the sector angle variable, and its value range is determined by the orientation set of the node object. It is used to generate the theoretical boundary of the view sector. Subsequently, the boundary of the occluded direction is clipped in combination with the occlusion relationship to obtain the actual view sector.

[0053] When extracting object subsets and generating object subset identifiers around each context domain identifier, the set of object identifiers directly covered by the context domain identifier is first read according to the inclusion relationship index. Then, the building objects, interface objects, street objects, plot objects, node objects, and underground impact objects that should be included within the context domain identifier are supplemented according to the object type dictionary, so that the object subset has complete cross-type expression capabilities. An object subset refers to a set of object identifiers that serve the same context domain identifier, and its boundary is not based on administrative boundaries or single control lines, but on the geometric coverage of the context domain identifier. Subsequently, a boundary buffer object set is constructed to handle boundary ambiguity and cross-domain coupling. The boundary buffer object set refers to a set of object identifiers that satisfy the requirements of the context domain identifier. The context domain identifier is a set of object identifiers that intersect with the boundary of the context domain identifier or are located within the influence radius of the context domain identifier. The influence radius is used to express the range of visual, traffic, or interface continuity impact of the context domain identifier on external objects. The influence radius can be jointly determined by the cross-sectional width of street objects, the field of view radius of node objects, and the boundary width of plot objects. Finally, an object subset identifier is generated for the object subset. The object subset identifier is used to uniquely identify the version of the object subset under the context domain identifier and records the composition list of the object subset and the composition list of the boundary buffer object set, so that the subsequent spatial relationship construction and state filtering can reuse a consistent set of objects under the same object subset identifier.

[0054] When constructing spatial relationship subsets based on object subset identifiers and generating spatial relationship subset identifiers, firstly, within the set of object identifiers defined by the object subset identifiers, adjacency relationships, occlusion relationships, line-of-sight relationships, and access relationships are extracted according to a unified spatial relationship dictionary. The spatial relationship dictionary refers to a set of rules that uniformly define spatial relationship types, directional semantics, and effective interval semantics. Adjacency relationships refer to the spatial relationship where the geometric carriers of two objects are in contact at the boundary, the distance is less than a threshold, or they share a boundary segment. Occlusion relationships refer to the spatial relationship where the interface or volume of one object obstructs the visibility of another object within the visual sector of a node object. Line-of-sight relationships refer to the visual corridor or visual endpoint relationship formed by the intersection of a ray from a node object along a specific direction with an interface object or building object. Access relationships refer to the relationship where the center lines of street objects connect... The system establishes reachable path relationships under the reachability constraints of node objects. For each spatial relationship, a spatial relationship record is generated. The spatial relationship record includes at least the relationship endpoint object identifier, relationship type, relationship direction, and relationship effective range. The relationship endpoint object identifier is used to determine the object pair affected by the relationship, the relationship type is used to determine the constraint semantics, the relationship direction is used to distinguish between unidirectional occlusion and bidirectional adjacency, and the relationship effective range is used to describe the effective range of the relationship in space or time. Finally, all spatial relationship records are aggregated to form a spatial relationship subset and a spatial relationship subset identifier is generated. The spatial relationship subset identifier is used to uniquely identify the version of the spatial relationship subset under the context domain identifier, so that subsequent candidate state pairing and statement activation can use the spatial relationship subset identifier as the unique spatial constraint input.

[0055] When constructing state subsets and generating state subset identifiers based on object subset identifiers and object state clusters, the object state cluster corresponding to each object identifier is first read within the object subset identifier. Then, the spatial relationship subset identifier is used as the constraint source to perform cross-object feasibility screening on candidate states. Candidate state pairing refers to enumerating candidate state combinations for object identifier pairs with spatial relationships and verifying whether the combination satisfies the geometric consistency, visual consistency, and reachability consistency constraints expressed by the spatial relationship record, thereby identifying the set of candidate states that can simultaneously hold true within the local context. To reduce the enumeration scale and improve verifiability, the feasibility of each candidate state pairing can be expressed using a pairing consistency score, and elimination or weighting is performed based on the pairing consistency score. The expression for the pairing consistency score is:

[0056] ;

[0057] in, Represents object identifier candidate states With object identifier candidate states The pairing consistency score ranges from 0 to 1, with higher values ​​indicating greater feasibility. It represents a logical function and is used to compress linear combinations into 0 to 1. Indicates the bias term. Indicates the first A set of satisfaction feature functions are used to characterize the degree of satisfaction of adjacency relationships, such as the consistency of interface continuity length, the preservation of visual corridor in occlusion relationships, the stability of visual endpoints in line-of-sight relationships, and the path reachability in passage relationships. Indicates the first Each satisfaction feature weight is fixed under the street identifier. Indicates the first A conflict characteristic function is used to characterize the degree of conflict, such as lane breakage, traffic obstruction, and enhanced view occlusion. Indicates the first Each conflicting feature has a weight and is fixed under the street identifier. Indicates the number of satisfying features. Indicates the number of conflicting features; when When the score is below a preset threshold, candidate states that participate in the low-scoring pair and lack any high-scoring alternative pair are marked as unavailable candidate states and are eliminated or downweighted. Finally, the available candidate states of each object identifier are gathered within the scope of the object subset identifier to form a state subset, and a state subset identifier is generated to record the composition of the state subset, the reason for elimination, and the basis for downweighting, thereby ensuring that subsequent statement subset extraction is based on the feasible state space rather than on a pseudo-state space that is locally infeasible.

[0058] When extracting statement subsets and generating statement subset identifiers based on the state subset identifier and trigger relationship mapping, the set of active statement identifiers indexed by object identifier and candidate state in the trigger relationship mapping is first read. Then, the corresponding active statement identifiers are filtered within the candidate state range defined by the state subset identifier, thus obtaining a statement set consistent with the local context. A statement subset refers to the set of constraint statements that are activated under the given object subset, state subset, and spatial relationship subset conditions. The difference between a statement subset and a constraint statement set is that a statement subset only retains statement identifiers that can be triggered under the current context domain identifier and whose applicable object domain falls within the object subset identifier. To ensure the interpretability of subsequent satisfiability determination, in addition to recording the statement identifier list, the statement subset identifier also records the adjudication strength, trigger condition hit summary, clause source, and evidence index attribute of each statement identifier. The trigger condition hit summary is used to explain why the statement identifier is activated under the state subset and spatial relationship subset. The clause source is used to refer back to the material identifier and paragraph index identifier. The evidence index attribute is used to refer back to the evidence fingerprint structure supporting the trigger in the object state cluster, thus enabling the statement subset identifier to have both computational usability and review traceability.

[0059] To generate local contexts and context identifiers, object subset identifiers, state subset identifiers, statement subset identifiers, and spatial relation subset identifiers are encapsulated. When forming a set of local contexts under a street identifier, the context domain identifier is first used as the spatial shell, the object subset identifier as the object shell, the spatial relation subset identifier as the spatial constraint shell, the state subset identifier as the state space shell, and the statement subset identifier as the rule shell for unified encapsulation. This generates context identifiers and establishes a subordinate relationship between context identifiers and street identifiers. A local context refers to a union of object subsets, spatial relation subsets, state subsets, and statement subsets within the same context domain identifier. A context identifier is an identifier used to uniquely identify the version of this union and is bound to a context version number and a verifiable index directory. The context version number is used to record the version of the object attribute set that the context identifier depends on. The document, object state cluster version, trigger relationship mapping version, and spatial relationship subset version are used to aggregate the material identifiers, paragraph index identifiers, and evidence index attributes involved in the context identifier. Then, under the street identifier, all context identifiers are gathered into a local context set, and coverage integrity verification and duplicate context merging are performed on the local context set. Coverage integrity verification is used to ensure that each object identifier in the spatial object set is covered by at least one context identifier and that the view sector of key node objects is fully covered by context domain identifiers. Duplicate context merging is used to merge context identifiers with highly overlapping object subset identifiers and highly consistent spatial relationship subset identifiers and update their version numbers, thereby forming a local context set that is controllable in scale, has complete coverage, and is verifiable, providing a stable computing unit for subsequent application of change identifiers and generation of change context identifiers.

[0060] S150. The renovation design scheme of the target historical block is parsed into a change identifier, and the change identifier is applied to the context identifier to update the state subset and recalculate the statement subset to obtain the change context identifier.

[0061] Specifically, when acquiring renovation design schemes for target historical blocks and creating design scheme records, planning drawings, architectural design drawings, interface improvement schemes, traffic organization schemes, equipment layout schemes, and public space adjustment schemes are compiled under the constraints of block identification. The design content from different carriers is then uniformly structured, converting it into a computable design scheme record. The design scheme record refers to the structured expression of the renovation design scheme, with fields covering at least element categories, geometric representations, functional representations, control representations, and source indexes. Layer semantics, annotation semantics, construction method semantics, and approval remarks semantics are merged into the same field system. An element identifier is generated for each design element in the design scheme record. This refers to a unique identifier that represents an operational design unit, and establishes a binding relationship between the element identifier and the object identifier in the spatial object set, so that each design element can refer back to the building object, interface object, street object, plot object, node object, or underground impact object in which it acts; element geometric description refers to the expression of the shape, position, direction and range of the design element; element functional description refers to the expression of the purpose, accessibility, operation or public nature of the design element; design control description refers to the expression of the control intentions for height, setback, material, color, opening, external equipment, traffic organization or public space organization, etc., thereby providing a stable data entry and a verifiable semantic source for subsequent design change analysis.

[0062] When performing design change parsing on element identifiers based on design scheme records to generate change identifiers, the design scheme records are aligned with the object attribute records of the object attribute set. This ensures that each element identifier forms a comparable structure between its pre-design and post-design states at the object identifier granularity. A change identifier is an identifier used to uniquely represent a design change operation and maintains a traceable association with the element identifiers. The set of affected objects refers to the set of object identifiers directly or indirectly affected by this change identifier. Directly affected objects are obtained by binding to element identifiers, while indirectly affected objects are derived from the spatial influence range description. The attribute change description set refers to the spatial geometry in the object attribute records. The system includes a set of change fields for attributes, age-level attributes, landscape element attributes, ownership and usage attributes, and standard application attributes, and records the values ​​before, after, and based on the changes for each change field; a state migration description set, which describes the migration of candidate states in an object's state cluster under the influence of changes, used to express the enhancement, weakening, replacement, and disabling of candidate states; and a spatial influence range description, which expresses the spatial range of influence of the change identifier on adjacency, occlusion, line-of-sight, and access relationships, and can be bound to the effective range of spatial relationship records, so that the change identifier simultaneously has the expression of change at the field level and the expression of propagation boundaries at the spatial coupling level.

[0063] When establishing a context change mapping record based on the set of objects affected by the change identifier and the subset identifiers of objects in the context identifier, the context identifiers are traversed under the constraint of the street identifier, and the subset identifiers of objects and the set of boundary buffer objects are read. The intersection matching of the set of objects affected by the change identifier and the subset identifiers of objects is performed, and at the same time, neighborhood hit matching is performed on the set of boundary buffer objects to cover cross-domain coupling in the fuzzy boundary area. The context change mapping record refers to the structured record of the interaction relationship between the change identifier and the context identifier. It contains at least the context identifier, the change identifier, the set of hit object identifiers, the hit type flag, and the hit evidence index attribute. The hit type flag is used to distinguish whether the object identifier belongs to the subset identifier hit or belongs to the set of boundary buffer objects hit. When the object identifier in the set of objects affected belongs to the subset identifier or is located in the set of boundary buffer objects, the change identifier is marked as a valid change identifier of the context identifier and written into the context change mapping record, so that subsequent state transition updates only occur within the context identifiers that are effectively affected, thereby avoiding the statement subset drift caused by the erroneous updating of irrelevant context identifiers.

[0064] When performing state migration update processing on state subsets based on context change mapping records to form updated state subset identifiers, the state subset identifiers corresponding to the context identifiers are read, and the state migration description set and attribute change description set are applied within their candidate state range to complete the field-by-field update of candidate state fields. Field update refers to replacing, adjusting intervals, or rewriting the structure of field values ​​in spatial geometric state, chronological level state, landscape element state, ownership and use state, and standard application state, and writing the update results back to the state field set of candidate states. Consistency adjustment refers to performing linked updates and feasibility re-checks on candidate states corresponding to adjacent object identifiers or boundary buffer object sets within the influence range defined by the spatial influence range description, in order to eliminate adjacency relationship breaks, occlusion relationship abrupt changes, line-of-sight relationship distortion, or passage relationship blockage caused by local changes. To ensure that consistency adjustment is based on verifiable quantitative judgment, a neighborhood consistency risk score containing spatial relationship propagation, evidence support, and time decay is constructed for each candidate state, and weighting or elimination is performed based on this score. The expression for the neighborhood consistency risk score is:

[0065] ;

[0066] in, Indicates candidate state The neighborhood consistency risk score ranges from 0 to 1, with a larger value indicating a greater need for consistency adjustments. This represents a logic function used to compress linear combinations into 0 to 1; Indicates the bias term. and arrive The weighting coefficients are represented and fixed under the street identifier; Indicates candidate state The object identifier index to which it belongs; Represents the set of adjacent object identifiers as defined by the spatial influence range description; Represents object identifier To object identifier The propagation weight is determined by the relationship type, relationship direction, and effective relationship range, and can be assigned higher weights according to occlusion relationship and passage relationship. Represents object identifier In candidate state The state vector is obtained by concatenating the field codes of spatial geometric state, chronological level state, landscape element state, ownership and use state, and standard application state. Represents object identifier Alignment candidate states are selected within the updated state subset, and the alignment candidate states are determined by the consistent maximum pairing under the spatial relation record constraint. Indicates the first The nth projection matrix is ​​used to project the state vector difference onto the nth projection matrix. To improve interpretability, subspaces corresponding to class-space relationships or control elements are defined. This represents the L2 norm, used to measure the magnitude of projection differences. Used to suppress the excessive amplification of overall risk by outliers; The strength of evidence support is represented by the convergence of the consistency summary of the evidence fingerprint and the source credibility label, and the value ranges from 0 to 1. The greater the strength of evidence support, the more stable the candidate state is. The time drift penalty is generated by the degree of deviation between the evidence time coverage interval and the center of the current effective time window, and its value ranges from 0 to 1. The penalty for evidence conflict is generated by the proportion of mutually exclusive values ​​given by different pieces of evidence for the same field, with a value range from 0 to 1. The principle behind this formula is to propagate the differences in the state vector caused by changes along the neighborhood and converge them into a risk term. Simultaneously, it uses the strength of evidence support to offset the risk and time drift and evidence conflict to enhance the risk, ensuring that consistency adjustments are both responsive to spatially coupled propagation and constrained by evidence. When the value exceeds a preset threshold, the candidate state is downweighted or eliminated to ensure that the updated state subset still satisfies the spatial relation subset constraint. After completing the field update and consistency adjustment, an updated state subset identifier is generated. The updated state subset identifier is used to uniquely identify the updated candidate state set version and records the update reason index corresponding to the context change mapping record.

[0067] When recalculating the statement subset based on the updated state subset identifier and trigger relationship mapping to generate updated statement subset identifiers, the index space of the trigger relationship mapping is replaced with the candidate state set limited by the updated state subset identifier. The validity of the state field constraint set and the spatial relationship subset constraint set under the updated state subset is re-examined for each statement identifier. Simultaneously, the evidence fingerprint threshold and approval history matching conditions are recalculated for statement identifiers containing exceptional conditions to ensure consistency between the activation state of exceptional conditions and the change in adjudication intensity. To enhance trigger stability in areas with ambiguous boundaries, statement activation determination is expressed as a trigger posterior probability including multi-source conditional attention, mutual exclusion penalty, and exceptional evidence threshold. A statement identifier is determined to be activated when the trigger posterior probability is not lower than the trigger threshold. The expression for the trigger posterior probability is:

[0068] ;

[0069] ;

[0070] in, This represents the posterior probability of triggering a statement identifier under the conditions of updating the subset of states and the subset of spatial relationships. The value ranges from 0 to 1, and the larger the value, the more likely it should be determined as an activated statement identifier. Represents a logical function; Indicates the bias term. and arrive The weighting coefficients are represented and fixed in the trigger table; This represents the set of trigger condition evidence features, which is obtained by concatenating state field matching evidence, spatial relationship matching evidence, and condition coverage evidence. Indicates the number of evidentiary features; Representing the feature projection dimension and by and The number of columns is determined; Indicates the first The condition vector of the sub-condition is used to express the applicable object domain, triggering conditions, and spatial relation subset constraint set of the first... The semantics of class constraints; and The projection matrix is ​​represented and fixed in the trigger table, and is used to project the condition vector and evidence features into the comparable space; Represents the value vector weights, used to map evidence features into summable scalar contributions; Indicates the first The attention aggregation score of the sub-condition indicates that the sub-condition is well supported by evidence; The threshold strength of exceptional evidence is determined by the convergence of the consistency summary of the evidence fingerprint of the candidate state, the source credibility label, the completeness of the verifiable location index, and the matching conditions of the approval history, and its value ranges from 0 to 1. This represents the mutual exclusion penalty, which is generated by the proportion of mutually exclusive propositions between the candidate state and the triggering condition, and its value ranges from 0 to 1. This represents the condition gap penalty, which is generated by the proportion of key sub-conditions that were not hit in the triggering condition and has a value range of 0 to 1. The time drift penalty is generated by the deviation between the evidence time coverage interval and the current effective time window, and its value ranges from 0 to 1. The principle of the above formula is to use an attention mechanism to aggregate the support of multiple sub-conditions for multi-source evidence into an interpretable contribution term, while taking the exception evidence threshold as a positive support term and mutual exclusion, gaps, and time drift as suppression terms, thereby obtaining the trigger posterior probability. and in When the threshold for triggering is not lower than the threshold for the trigger table, the statement identifier is written into the update statement subset identifier; otherwise, it is removed from the update statement subset identifier. In addition to the list of statement identifiers, the update statement subset identifier also records the trigger condition hit summary, clause source, and evidence index attributes to maintain verifiability.

[0071] When encapsulating the context identifier, update state subset identifier, update statement subset identifier, and context change mapping record to generate a changed context identifier, and generating the context version number and change index record, the context identifier is used as the pre-change baseline shell, the update state subset identifier as the post-change state shell, the update statement subset identifier as the post-change rule shell, and the context change mapping record as the change source shell, to form the changed context identifier. The changed context identifier refers to the context instance identifier obtained under the same context domain identifier due to the application of a valid set of change identifiers. The context version number is used to mark the version information of the changed context identifier, and it includes at least the context identifier version number and the update state subset identifier. The version number, update statement subset version number, and trigger relationship mapping version number are used to enable any change context identifier to trace back to the state generation logic and rule triggering logic it depends on. The change index record is used to index which change identifiers trigger the change context identifier, which object identifiers are hit, which spatial relationship records are affected, and which statement identifiers have their activation status changed. The change index record contains at least a set of change identifiers, a set of hit object identifiers, a summary of the scope of influence, and an update timestamp. This allows subsequent satisfiability determination to directly use the change context identifier as a unified input, and to quickly trace back to the target change subset and its action path along the change index record when it is determined to be unsatisfiable.

[0072] S160. Perform a satisfiability determination on the change scenario identifier. When the determination result is unsatisfiable, extract the corresponding design conflict features and output the set of statements that the target cannot be simultaneously established and the target change subset. Construct a conflict association hypergraph based on the set of statements that the target cannot be simultaneously established and the target change subset to complete the extraction and association determination of design conflict features for the renovation of historical blocks.

[0073] Specifically, when establishing a satisfiability determination context for each change context identifier, the object subset identifier, update state subset identifier, update statement subset identifier, and spatial relationship subset identifier encapsulated by the change context identifier are first read under the street identifier constraint. The context change mapping record and change index record are then included in the same context carrier, making this context carrier the sole data entry point for subsequent satisfiability determination and unsatisfiability tracing. The satisfiability determination context refers to the information closure formed around a single change context identifier, used to ensure that no out-of-context object identifiers or out-of-context statement identifiers are introduced during the determination process. The object subset identifier refers to the version identifier of the set of object identifiers within the context domain identifier and the boundary buffer object set. The update state subset identifier refers to the object... The subset identifier is the version identifier of the set of available candidate states for each object identifier within the subset identifier range; the update statement subset identifier refers to the version identifier of the set of statement identifiers activated under the conditions of the update state subset identifier and the spatial relationship subset identifier; the spatial relationship subset identifier refers to the version identifier of the set of spatial relationship records of adjacency, occlusion, line-of-sight, and passage relationships between object identifiers within the object subset identifier; the context change mapping record refers to the set of object identifiers that the change identifier hits the context identifier and the hit type marker; the change index record refers to the index set of the change identifier set, the set of hit object identifiers, the scope of influence summary, and the trigger change summary, so that subsequent unsatisfiable proofs can trace back to the target change subset along the change index record and maintain the verifiability of the evidence chain.

[0074] When constructing a statement constraint set and generating constraint set identifiers based on the updated statement subset identifiers, the process first iterates through each statement identifier in the updated statement subset identifiers and loads its applicable object domain, triggering condition, exception condition, adjudication strength, clause source, and evidence index attributes. Then, the applicable object domain is mapped to the set of object identifiers within the object subset identifier. The mapping result is used to determine the subset of object identifiers in which the statement identifier functions in this context. Next, the triggering condition is mapped to the candidate state field constraints within the updated state subset identifier. Candidate state field constraints refer to the selection of fields for spatial geometric state, chronological level state, landscape element state, ownership and use state, and normative application state. The constraint expression of values, field ranges, or field combinations; then the spatial relation subset constraint set is mapped to the spatial relation record in the spatial relation subset identifier, so that the spatial triggering premise of the statement identifier can be directly retrieved by relation endpoint object identifier, relation type, relation direction, and relation valid range; the statement constraint set refers to the structured set of converting the statement identifier from text semantics into searchable object constraints, state constraints, and spatial constraints; the constraint set identifier refers to the version identifier of the statement constraint set and binds the adjudication strength and exception condition threshold, so that subsequent satisfiability search can distinguish between hard adjudication statements and soft adjudication statements and adopt a consistent threshold judgment caliber for exception conditions.

[0075] When constructing the context assignment space based on the constraint set identifier and generating the assignment space identifier, the candidate state set corresponding to the updated state subset identifier is first read for each object identifier within the scope of the object subset identifier. Each candidate state is then encoded into a state vector for unified matching with the trigger condition field. The state vector is obtained by concatenating the field codes of spatial geometric state, chronological level state, landscape element state, ownership and use state, and standard application state. The context assignment space refers to the joint state space formed by selecting a candidate state for each object identifier within the object subset identifier. The assignment space identifier refers to the version identifier of the joint state space and records the size of the candidate state set and the distribution of the candidate state credibility level for each object identifier. To reduce search overhead and maintain verifiability, a matching index is established between the candidate state set and the trigger condition field in the statement constraint set. The matching index is a feasible candidate set mapping table from the statement identifier to the candidate state set. It is constructed by pre-checking whether the candidate state field satisfies the state field constraints of the statement identifier and whether the candidate state has the neighborhood pairing required to satisfy the spatial relationship constraints. This limits the enumeration domain of the subsequent satisfiability search to the feasible candidate set given by the matching index and reduces the combinatorial explosion caused by the boundary ambiguity region.

[0076] When performing a satisfiability search on the assignment space identifiers to generate satisfiability results, each statement identifier is treated as a satisfiability predicate for assigning a situation value. The search within the joint state space defined by the assignment space identifiers examines whether a set of candidate state choices exists such that all hard-judgment statements are simultaneously true. Soft-judgment statements are included in the optional satisfiability search, and an unresolved set is output when necessary. The satisfiability search can be implemented as a constraint-satisfiability search with backtracking. The coupling degree between the mandatory label of the statement constraint set and the spatial relation record is used as a variable selection heuristic, prioritizing the allocation of object identifiers that are more sensitive to spatial relations or have tighter constraints to improve pruning efficiency. To ensure the auditability of the search process, the satisfiability objective is written as minimizing the joint cost of violating both hard-judgment statements and soft-judgment statements, and determining satisfiability when the joint cost is zero. The expression for the joint cost is:

[0077] ;

[0078] in, This represents a context assignment, which consists of candidate states selected by each object identifier within the object subset identifier; This represents the set of hard ruling statement identifiers. This represents the set of soft adjudication statement identifiers; Indicates hard ruling statement identifier The weight is determined by the strength level of the ruling and the priority of the source of the clause, and the value range is positive. Indicates a soft ruling statement identifier The weight is determined by the strength level of the ruling and the degree to which the evidentiary threshold is met, and the value range is positive. This represents the soft decision weight scaling factor, which is a non-negative number and is used to control the impact of soft decisions on the total cost. This represents the set of endpoint object identifiers for spatial relation records within a spatial relation subset identifier. Represents object identifier pairs The spatial coupling weight is determined by the relation type, relation direction, and effective relation interval, and its value range is positive. This represents the scaling factor for space consistency penalty, and its value is a non-negative number. Indicates statement identifier Assigning values ​​in context The predicate whether the following condition is true or false is determined by the set of state field constraints and spatial relation subset constraints. Represents object identifier pairs Assigning values ​​in context The predicate that satisfies the spatial relation record constraint; The expression represents an indicator function, which takes a value of 1 if the condition within the parentheses is true and 0 otherwise. The above formula transforms statement violations and spatial relation violations into cumulative costs, enabling the search to output both the existence of a zero-cost solution and, when unsatisfiable, the conflict core that prevents the cost from being reduced to zero. When it is determined that no solution exists... When assigning a context value, an unsatisfiable proof is generated. An unsatisfiable proof refers to the set of minimum unsatisfiable statements and their corresponding triggering conditions that hit the summary, clause source, and evidence index attributes. Change identifiers associated with the minimum unsatisfiable statement set are extracted along the change index record to form a target change subset. This makes the target unsatisfiable statement set and the target change subset verifiable and traceable within the same change context identifier.

[0079] When extracting design conflict features and generating conflict identifiers based on the set of statements where targets cannot be simultaneously true, the following steps are taken: First, statement contradiction features are extracted from the set of statements where targets cannot be simultaneously true. Statement contradiction features refer to the structured contradiction patterns between statement identifiers in terms of adjudication strength, overlapping relationships of applicable object domains, mutual exclusion of triggering conditions, and compatibility of exception conditions. Next, state contradiction features corresponding to the statement contradiction features are extracted from the updated state subset identifiers. State contradiction features refer to the combination of state fields that cause statements to be triggered simultaneously but cannot be satisfied simultaneously, and their propagation paths among object identifiers. Then, spatial relationship contradiction features are extracted from the spatial relationship subset identifiers. Spatial relationship contradiction features refer to the contradiction patterns in which spatial relationship records of adjacency, occlusion, line-of-sight, or passage relationships impose mutually conflicting requirements on the same object identifier within the effective interval of the relationship, resulting in an unsolvable contradiction. To enable the conflict features to be used for association discrimination, the above three types of features are encoded into conflict feature vectors and conflict identifiers are generated. A conflict identifier is a unique identifier for a conflict instance and is bound to the set of statements where targets cannot be simultaneously true, the target change subset, the set of hit object identifiers, and the set of evidence index attributes, so that subsequent hypergraph construction can use the conflict identifier as the central node and maintain the complete link of conflict interpretation.

[0080] When constructing a conflict-related hypergraph and generating hypergraph identifiers based on the set of statements where the target cannot be simultaneously true and the target change subset, conflict identifiers, statement identifiers, change identifiers, object identifiers, and change context identifiers are used as the node set. A set of hyperedges is defined based on the set of statements where the target cannot be simultaneously true and the target change subset, allowing a single hyperedge to connect multiple statement identifiers or multiple change identifiers to express many-to-many causality. The conflict-related hypergraph refers to a relationship graph structure containing hyperedges. Statement hyperedges connect conflict identifiers to all statement identifiers in the set of statements where the target cannot be simultaneously true; change hyperedges connect conflict identifiers to all change identifiers in the target change subset; object-related edges connect conflict identifiers to the set of hit object identifiers; and context-related edges connect conflict identifiers to change context identifiers. To ensure the hypergraph can be used for subsequent similar conflict merging and homogeneous conflict cluster determination, each hyperedge is assigned a weight based on overlap and evidence threshold, and this weight is embedded in the hypergraph identifier. The expression for the hyperedge weight is:

[0081] ;

[0082] in, Indicates the superedge The weight of the superedge ranges from 0 to 1, and the larger the value, the stronger the contribution of the superedge to the conflict association determination. Represents a logical function; Indicates the bias term. to The weighting coefficients are represented and fixed under the street identifier; Indicates the superedge The set of connected nodes; Indicates the relationship with the hyperedge The reference superedge for correlation comparison can be the statement superedge and change superedge under the same conflict identifier, or the corresponding superedge in the same candidate conflict cluster. This represents the overlap of a set of nodes, with a value ranging from 0 to 1, and the higher the overlap, the larger the value. This indicates the strength of the evidence supporting the super-edge, with a value ranging from 0 to 1. It is obtained by combining the completeness of the source of the clauses associated with the super-edge and the verifiability of the evidence index attributes. The value of represents the heterogeneity penalty of the hyperedge, ranging from 0 to 1, and is obtained by the convergence of the dispersion of the node type distribution within the hyperedge and the mutual exclusivity of the triggering conditions. The superedge time drift penalty, ranging from 0 to 1, is obtained by converging the deviation between the evidence time coverage interval and the current effective time window. The above formula integrates structural overlap, evidence support, and penalty terms into weights, enabling the conflict association hypergraph to express both the structural association of the conflict and the robustness and temporal stability of the evidence. Finally, a hypergraph identifier is generated, which refers to the version identifier of the conflict association hypergraph and binds the node set, superedge set, superedge weight, and verifiable index directory, thereby completing the extraction and association discrimination of design conflict features for historical block renovation and providing stable input for subsequent output of homogeneous conflict clusters.

[0083] This application also provides a device for extracting and identifying design conflict features in the renovation of historical districts, referring to... Figure 2 , Figure 2This is a schematic diagram of a device for extracting and identifying design conflict features in the renovation of historical blocks, provided in an embodiment of this application. The device is a server, comprising an acquisition module 21 and a processing module 22. The acquisition module 21 acquires a set of spatial objects of the target historical block and establishes a block identifier. It generates an object identifier for each spatial object in the set and solidifies a set of object attributes, including spatial geometric attributes, chronological hierarchy attributes, landscape element attributes, ownership and usage attributes, regulatory applicability attributes, and evidence index attributes. The processing module 22 constructs an object state cluster around the object identifier and object attribute set. The object state cluster includes spatial geometric state, chronological hierarchy state, landscape element state, ownership and usage state, and regulatory applicability state. The processing module 22 also performs semantic decomposition on the protection list, landscape guidelines, control regulations, mandatory regulations, approval history, and site survey records of the target historical block to form a set of constraint statements. The processing module 22 establishes a trigger relationship mapping between the constraint statement set and the object state cluster. It also constructs a local context set and context identifier based on the street block identifier. The local context set consists of an object subset, a state subset, a statement subset, and a spatial relationship subset. The statement subset is formed by constraint statements activated under the conditions of the state subset and the spatial relationship subset through the trigger relationship mapping. Furthermore, the processing module 22 parses the renovation design scheme of the target historical street block into a change identifier and applies the change identifier to the context identifier to update the state subset and recalculate the statement subset, thus obtaining the changed context identifier. Finally, the processing module 22 performs a satisfiability determination on the changed context identifier. When the determination result is unsatisfiable, it extracts the corresponding design conflict features and outputs the target non-simultaneously valid statement set and the target change subset. It then constructs a conflict association hypergraph based on the target non-simultaneously valid statement set and the target change subset to complete the extraction and association discrimination of design conflict features for the renovation of the historical street block.

[0084] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0085] This application also provides an electronic device, with reference to... Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: at least one processor 31, at least one network interface 34, a user interface 33, a memory 35, and at least one communication bus 32.

[0086] The communication bus 32 is used to enable communication between these components.

[0087] The user interface 33 may include a display screen and a camera. Optionally, the user interface 33 may also include a standard wired interface and a wireless interface.

[0088] The network interface 34 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0089] The processor 31 may include one or more processing cores. The processor 31 connects to various parts of the server via various interfaces and lines, executing instructions, programs, code sets, or instruction sets stored in the memory 35, and calling data stored in the memory 35 to perform various server functions and process data. Optionally, the processor 31 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 31 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content to be displayed on the screen; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 31 and may be implemented as a separate chip.

[0090] The memory 35 may include random access memory (RAM) or read-only memory. Optionally, the memory 35 may include a non-transitory computer-readable storage medium. The memory 35 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 35 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 35 may also be at least one storage device located remotely from the aforementioned processor 31. Figure 3 As shown, the memory 35, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for extracting and identifying design conflict features in the renovation of historical districts.

[0091] exist Figure 3 In the electronic device shown, the user interface 33 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 31 can be used to call the application program stored in the memory 35, which is a method for extracting and identifying design conflict features of historical district renovation. When executed by one or more processors, the electronic device executes one or more methods as described in the above embodiments.

[0092] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0093] This application also provides a non-transitory computer-readable storage medium storing instructions. When executed by one or more processors, these instructions cause an electronic device to perform one or more of the methods described in the above embodiments.

[0094] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0095] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings or direct couplings or communication connections may be through some service interfaces; indirect couplings or communication connections between apparatuses or units may be electrical or other forms.

[0096] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0097] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0098] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0099] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of other embodiments of this disclosure upon considering the specification and the disclosure of practical truth. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for extracting and identifying design conflict features in the renovation of historical districts, characterized in that, The method includes: Obtain a set of spatial objects for the target historical district and establish a district identifier. Generate an object identifier for each spatial object in the set of spatial objects and solidify a set of object attributes. The set of object attributes includes spatial geometric attributes, age hierarchy attributes, landscape element attributes, ownership and use attributes, regulatory applicability attributes, and evidence index attributes. An object state cluster is constructed around the object identifier and the object attribute set. The object state cluster includes spatial geometric state, chronological level state, landscape element state, ownership and usage state, and standard application state. Semantic decomposition is performed on the protection list, style guidelines, control plan clauses, mandatory norms, approval history and survey records of the target historical blocks to form a set of constraint statements, and a trigger relationship mapping is established between the set of constraint statements and the object state cluster; Based on the street identifier, a local context set and context identifier are constructed. The local context set consists of an object subset, a state subset, a statement subset, and a spatial relationship subset. The statement subset is formed by the constraint statements activated under the conditions of the state subset and the spatial relationship subset, which are mapped by the trigger relationship. The renovation design scheme of the target historical block is parsed into a change identifier, and the change identifier is applied to the context identifier to update the state subset and recalculate the statement subset to obtain the change context identifier; A satisfiability determination is performed on the changed scenario identifier. When the determination result is unsatisfiable, the corresponding design conflict features are extracted, and a set of statements indicating that the objectives cannot be simultaneously met and a subset of target changes are output. A conflict association hypergraph is then constructed based on the set of statements indicating that the objectives cannot be simultaneously met and the subset of target changes to complete the extraction and association discrimination of design conflict features for the renovation of historical blocks. Specifically, this includes: A satisfiability determination context is established for each of the aforementioned change context identifiers. The satisfiability determination context includes object subset identifiers, update state subset identifiers, update statement subset identifiers, spatial relationship subset identifiers, context change mapping records, and change index records. Based on the update statement subset identifier, a statement constraint set is constructed and a constraint set identifier is generated. The applicable object domain of each statement identifier is mapped to the object identifier set within the object subset identifier. The triggering condition is mapped to the candidate state field constraint within the update state subset identifier. The spatial relationship subset constraint set is mapped to the spatial relationship record in the spatial relationship subset identifier. Based on the constraint set identifier, a scenario assignment space is constructed and an assignment space identifier is generated. The scenario assignment space consists of a set of candidate states corresponding to the object identifiers within the object subset identifier, and a matching index is established between the set of candidate states and the trigger condition fields in the statement constraint set. Perform a satisfiability search on the assignment space identifier to generate a satisfiability result. When the satisfiability result is unsatisfiable, generate an unsatisfiability proof and output a set of statements that the target cannot be simultaneously true and a subset of target changes. Based on the set of statements where the objectives cannot be simultaneously met, extract statement contradiction features, state contradiction features, and spatial relationship contradiction features to form design conflict features and generate conflict identifiers; Based on the set of statements that cannot be simultaneously established for the stated objectives and the subset of statements that change for the stated objectives, a conflict association hypergraph is constructed and a hypergraph identifier is generated to complete the extraction and association discrimination of design conflict features for the renovation of historical blocks.

2. The method for extracting and identifying design conflict features in the renovation of historical districts according to claim 1, characterized in that, The process of acquiring a set of spatial objects for the target historical district and establishing a district identifier, and generating an object identifier for each spatial object in the set of spatial objects and fixing the set of object attributes, specifically includes: Under the constraints of the street identifier, a set of spatial objects is constructed, and an object identifier is assigned to each spatial object in the set of spatial objects. The object identifier establishes a unique correspondence with the geometric carrier of the corresponding spatial object. The set of spatial objects includes building objects, interface objects, street and alley objects, plot objects, node objects, and underground influence objects. Construct an initial set of object attributes based on the object identifier; Cross-source alignment and deduplication are performed on the initial object attribute set. The cross-source alignment includes coordinate benchmark unification, time label unification, and scale unification. The deduplication includes geometric overlap discrimination, name alias merging discrimination, and evidence index consistency discrimination to ensure that each spatial object corresponds to only one unique object identifier. A consistency solidification process is performed on the initial object attribute set, wherein the consistency solidification process includes field completeness check, field conflict check and evidence threshold check, and the attribute fields in the initial object attribute set are divided into a definite area and an uncertain area according to the check results, so as to form an object attribute set corresponding to the street identifier.

3. The method for extracting and identifying design conflict features in the renovation of historical districts according to claim 1, characterized in that, The construction of the object state cluster around the object identifier and the object attribute set specifically includes: Under the street identifier constraint, a state generation context is established for each object identifier. The state generation context includes the object attribute record corresponding to the object identifier, the definite area and the uncertain area of ​​the object attribute record, the evidence index attribute of the object attribute record, and the set of adjacent object identifiers that have a spatial relationship with the object identifier. Based on the state generation context, candidate state enumeration is performed to form an initial object state cluster. The candidate state enumeration combines and expands the uncertain areas of the object attribute records according to the object type dictionary and field dependency graph to generate multiple candidate states. Each candidate state includes spatial geometric state, chronological level state, landscape element state, ownership and use state, and standard application state. For each candidate state, an evidence fingerprint and a credibility level are generated. The evidence fingerprint is formed by aggregating the evidence index attribute set corresponding to the candidate state according to the source type, time coverage interval and consistency summary. The credibility level is determined by the evidence consistency summary, evidence time coverage interval and evidence source credibility label in the evidence fingerprint. The initial object state cluster is subjected to spatial relation consistency filtering and specification application consistency convergence processing, and the object state cluster is generated by combining the evidence fingerprint and the trust level.

4. The method for extracting and identifying design conflict features in the renovation of historical districts according to claim 1, characterized in that, The process involves semantically decomposing the protection list, style guidelines, control plan clauses, mandatory regulations, approval history, and site survey records of the target historical district to form a set of constraint statements. A trigger relationship mapping is then established between this set of constraint statements and the object state cluster. Specifically, this includes: Under the constraints of the street identification, the protection list, landscape guidelines, control plan clauses, mandatory regulations, approval history and survey records are collected and a rule evidence catalog is established. Material identification is generated for each source material and bound to the time coverage period, applicable geographical scope, issuing entity and verifiable location index. Text normalization is performed on each material identifier in the rule evidence catalog to form normalized text, and paragraph index identifiers are generated for the paragraph sequences in the normalized text; Semantic decomposition is performed based on the standardized text to form the set of constraint statements and generate statement identifiers. Each constraint statement includes the applicable object domain, triggering condition, exception condition, adjudication strength, clause source and evidence index attributes. The constraint statement set is subjected to terminology alignment and alias merging processing, and the object names and spatial relationship terms in the constraint statements are uniformly mapped based on the field system of the object type dictionary and the object attribute set. Construct a trigger table, which uses statement identifier as the primary key, maps the applicable object domain to a set of object types, maps the trigger conditions to a set of status field constraints and a set of spatial relationship subset constraints, and maps the exception conditions to evidence fingerprint thresholds and approval history matching conditions. Based on the trigger table, a trigger relationship mapping is established between the set of constraint statements and the object state cluster.

5. The method for extracting and identifying design conflict features in the renovation of historical districts according to claim 1, characterized in that, The construction of a local context set and context identifiers based on the street identifiers specifically includes: Under the constraints of the street block identifier, a context domain division rule is constructed and a context domain identifier is generated. The context domain identifier is jointly determined by the arc length segment of the street object, the view sector of the node object, and the boundary zone of the plot object. An inclusion relationship index is established between the context domain identifier and the object identifier in the spatial object set. A subset of objects is extracted around each of the aforementioned context domain identifiers and an object subset identifier is generated. The object subset includes building objects, interface objects, street and alley objects, plot objects, node objects, and underground influence objects within the scope of the context domain identifier. Object identifiers that intersect with the boundary of the context domain identifier or are located within the influence radius of the context domain identifier are included in the object subset to form a boundary buffer object set. Based on the object subset identifier, a spatial relationship subset is constructed and a spatial relationship subset identifier is generated. The spatial relationship subset includes the adjacency relationship, occlusion relationship, line-of-sight relationship and passage relationship between object identifiers within the object subset. For each spatial relationship, a spatial relationship record is generated that includes the object identifier of the relationship endpoint, the relationship type, the relationship direction and the effective range of the relationship. Based on the object subset identifier and the object state cluster, a state subset is constructed and a state subset identifier is generated. By performing candidate state pairing on object identifiers with spatial relationships and checking the spatial relationship subset constraint satisfaction, candidate states that cannot form feasible pairings are eliminated or downweighted. Based on the mapping between the state subset identifier and the triggering relationship, a statement subset is extracted and a statement subset identifier is generated. The statement subset is composed of the activation statement identifier corresponding to the object subset under the state subset condition. The object subset identifier, state subset identifier, statement subset identifier, and spatial relationship subset identifier are encapsulated to generate local contexts and context identifiers, and a set of local contexts is formed under the street identifier.

6. The method for extracting and identifying design conflict features in the renovation of historical districts according to claim 1, characterized in that, The process of parsing the renovation design scheme of the target historical block into a change identifier, and applying the change identifier to the context identifier to update the state subset and recalculate the statement subset to obtain the change context identifier specifically includes: Obtain the renovation design scheme of the target historical block, and perform structured processing on the planning drawings, architectural design drawings, interface improvement scheme, traffic organization scheme, equipment layout scheme and public space adjustment scheme in the renovation design scheme to form a design scheme record. Generate element identifier for each design element in the design scheme record. The element identifier is bound to the object identifier, element geometric description, element functional description and design control description in the spatial object set. Based on the design scheme record, the element identifier is subjected to design change parsing processing to generate a change identifier. The change identifier includes a set of objects affected, a set of attribute change descriptions, a set of state transition descriptions, and a description of spatial impact range. Establish a context change mapping record based on the set of objects affected in the change identifier and the object subset identifier in the context identifier. When the object identifier in the set of objects affected belongs to the object subset identifier or is located in the boundary buffer object set, mark the change identifier as a valid change identifier of the context identifier. Based on the context change mapping record, state migration update processing is performed on the state subset. Based on the state migration description set and the attribute change description set, the candidate states in the state subset are updated with fields. Based on the spatial influence range description, the candidate states corresponding to the adjacent object identifier or the boundary buffer object set are adjusted for consistency to form an updated state subset identifier. Based on the mapping between the updated state subset identifier and the triggering relationship, the statement subset is recalculated to generate the updated statement subset identifier; The context identifier, update state subset identifier, update statement subset identifier, and context change mapping record are encapsulated to generate a change context identifier, and a context version number and change index record corresponding to the change context identifier are generated.

7. A device for extracting and identifying design conflict features in the renovation of historical districts, characterized in that, The device is used to perform the method for extracting and identifying design conflict features in the renovation of historical districts as described in any one of claims 1 to 6. The device includes an acquisition module and a processing module, wherein... The acquisition module is used to acquire a set of spatial objects of the target historical block and establish a block identifier, and generate an object identifier for each spatial object in the set of spatial objects and solidify a set of object attributes. The set of object attributes includes spatial geometric attributes, age hierarchy attributes, landscape element attributes, ownership and use attributes, standard application attributes, and evidence index attributes. The processing module is used to construct an object state cluster around the object identifier and the object attribute set. The object state cluster includes spatial geometric state, chronological hierarchical state, landscape element state, ownership and usage state, and standard application state. The processing module is also used to perform semantic decomposition on the protection list, style guidelines, control regulations, mandatory norms, approval history and survey records of the target historical blocks to form a set of constraint statements, and to establish a trigger relationship mapping between the set of constraint statements and the object state cluster; The processing module is also used to construct a local context set and a context identifier based on the street identifier. The local context set consists of an object subset, a state subset, a statement subset and a spatial relationship subset. The statement subset is formed by the constraint statements activated under the conditions of the state subset and the spatial relationship subset, which are mapped by the trigger relationship. The processing module is further configured to parse the renovation design scheme of the target historical block into a change identifier, and apply the change identifier to the context identifier to update the state subset and recalculate the statement subset to obtain the change context identifier; The processing module is further configured to perform a satisfiability determination on the change scenario identifier. When the determination result is determined to be unsatisfiable, the module extracts the corresponding design conflict features and outputs a set of statements that the target cannot be simultaneously established and a subset of target changes. The module then constructs a conflict association hypergraph based on the set of statements that the target cannot be simultaneously established and the subset of target changes to complete the extraction and association determination of design conflict features for the renovation of historical blocks.

8. An electronic device, characterized in that, The electronic device includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions. The user interface and the network interface are both used to communicate with other devices. The processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores instructions that, when executed, perform the method as described in any one of claims 1 to 6.

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