Water conservancy design decision support system based on knowledge graph

Abstract

The invention relates to the technical field of engineering design management, in particular to a water conservancy design decision support system based on a knowledge graph, which comprises a parameter constraint construction module, a design standard fusion module, a task semantic affiliation module, a path screening closing module and a structure combination response module. According to the method, logic linkage organization among structure parameters is realized by constructing a parameter control path and combining with multi-relationship identification among structure nodes, a cross relationship judgment mechanism among standard terms is utilized, the constraint identification capability on the structure control path is enhanced, and the structure control path is identified by combining with an index relationship of task semantic tags. Structural path screening has semantic guiding characteristics, a continuity judgment method of a closed path is adopted, structural matching precision of path screening is optimized, logic is constructed by using response of a structural combination relation, collaborative adaptability among multiple structures is improved, a linkage path with continuity and logical attachment characteristics is established, and the structural path screening efficiency is improved. And the logic integrity and response coordination of water conservancy design are improved.

Description

Technical Field

[0001] This invention relates to the field of engineering design management technology, and in particular to a knowledge graph-based hydraulic design decision support system. Background Technology

[0002] The field of engineering design management technology encompasses the systematic organization and management of various information, resources, processes, and tasks involved in the entire process of engineering projects, from planning and design to execution. This includes design scheme development, project task allocation, design resource scheduling, design process monitoring, version management, and design collaboration. Its aim is to improve the efficiency and quality of engineering design through scientific management methods while meeting functional and regulatory requirements. In practical engineering, engineering design management technology combines information systems and modeling tools to construct decision support models oriented towards the design process, assisting designers in multi-source data analysis, design logic organization, and scheme development. It also involves the structured modeling of design knowledge, the standardized management of design standards, and the establishment of cross-disciplinary collaboration mechanisms. By integrating information modeling, knowledge organization, and intelligent reasoning methods, it enables engineering design activities to achieve [the desired results]. The system provides information and intelligent support, among which, the knowledge graph-based water conservancy design decision support system refers to the use of knowledge graph technology to construct a knowledge model system in the field of water conservancy engineering design, and based on this model, it provides the auxiliary decision-making capabilities required in the design stage. For technical matters involved in water conservancy design, such as design specifications, structural types, hydrological parameters, geological conditions and construction schemes, entity extraction and relation modeling are performed through water conservancy engineering-related standards and historical project data to construct a water conservancy design knowledge graph. Subsequently, the semantic relation network in the graph is used to perform design task matching, parameter recommendation and structural combination analysis, and the optimal design path is inferred in combination with design working conditions. Through entity recognition, relation extraction, graph construction and inference engine, the system realizes the organization, reasoning and application support of water conservancy design knowledge, and provides knowledge association and judgment basis in the design management process.

[0003] Traditional hydraulic design decision support technologies typically rely on static knowledge modeling when processing hydraulic design processes. This approach fails to effectively quantify the linkage constraints between structural nodes and parameters. When faced with the cross-influence between multiple nodes and the uncertainty of semantic control paths in structural design scenarios, it cannot clearly define the control direction and influence path between parameters. Furthermore, it suffers from insufficient coverage of control relationships during the adaptation of standard clauses. Moreover, it fails to introduce a mapping structure between master control nodes and functional parameters in the generation of task semantic control paths, resulting in low path matching accuracy. Structural combination analysis lacks a correlation judgment mechanism based on actual working conditions. In the construction involving the relationship between dam inclination angle and diversion section, it lacks a proportional quantification and path continuity verification mechanism, affecting the completeness of the structural response path establishment. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing a knowledge graph-based hydraulic design decision support system.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a knowledge graph-based hydraulic design decision support system includes: The parameter constraint construction module calls the engineering survey data interface to analyze the engineering attributes of various survey data and their role paths in the design, calculates the linkage relationship between rock layer strength and lining thickness and establishes parameter control paths, calibrates the constraint transmission chain between structural nodes, and obtains the parameter logical dependent structure. The design standard fusion module utilizes the parameter logic dependency structure to analyze the control boundary between structural nodes and design parameters, retrieve constraint clauses for structural parameters in the standard text, calculate control combinations between controlled parameters and establish connection paths, identify structural nodes with common control paths, and obtain the index logic fusion density. Based on the logical fusion density of the indicators, the task semantic attribution module analyzes the functional distribution of structural nodes in the task description, identifies the dominant parameter control path and matches task semantic keywords, establishes the index relationship between semantic tags and master control nodes, and obtains master control semantic identification tags. The path filtering and closure module analyzes the set of path parameters associated with the master control node in the graph based on the master control semantic recognition tag, calculates the continuous connection relationship between the parameters and filters the set of valid paths to obtain the path closure structure record; Based on the path closure structure record, the structural combination response module analyzes the multi-structure combination relationship within the continuous path segment, extracts structural nodes including the dam body, diversion channel and spillway, calculates the geometric correspondence and control ratio between structures, establishes response connection paths and records path information, and obtains combined response coordination information.

[0006] As a further embodiment of the present invention, the parameter logic dependency structure includes the head parameter control boundary, the permeability intensity linkage relationship, and the structural node dependency path; the index logic fusion density specifically includes the structural parameter control number distribution, the standard clause control hierarchy, and the boundary intersection identifier between clauses; the master control semantic identification label includes the function control label, the semantic master control path identifier, and the task entry mapping sequence; the path closure structure record specifically includes the structural path connection information, the boundary alignment matching order, and the path number filtering list; and the combined response coordination information includes the structural node response sequence, the combined control ratio relationship, and the connection path index information.

[0007] As a further aspect of the present invention, the parameter constraint construction module includes: The survey parameter identification submodule calls the engineering survey data interface to analyze the engineering attributes of various survey data and their role in the design, including water head height, permeability coefficient and rock strength. It determines the coupling trend between the variation range of permeability coefficient at the stratigraphic boundary and the rate of change of rock strength, establishes an engineering attribute matching table between hydrological permeability characteristics and rock mass structure response, and obtains the reference value of the survey parameter response relationship. The control relationship derivation submodule analyzes the stability of the response effect of rock layer strength change on lining thickness based on the reference value of the response relationship of the survey parameters, calculates the boundary coupling state between rock layer strength, water head height and permeability coefficient, calculates the constraint strength value of the linkage structure, determines the response transmission direction between linkage structures, and generates linkage parameter action coefficients. The path dependency construction submodule analyzes the logical dependency order of the control path and establishes directional connections between nodes based on the linkage parameter action coefficient, records the parameter source information associated with the control path, identifies and marks the constraint transmission chain between structural nodes, and obtains the parameter logical dependency structure.

[0008] As a further aspect of the present invention, the design standard fusion module includes: The clause attribution determination submodule obtains the parameter logical dependency structure, analyzes the control boundary between structural nodes and design parameters, retrieves the constraint clauses of structural parameters in the standard text, including protective layer thickness, foundation width and cross-sectional dimensions, determines the control attribution relationship of the standard item corresponding to the structural node, identifies the parameter correspondence between the structural node and the design clause, establishes the attribution distribution between the structural node and the standard clause, and obtains the standard attribution distribution value. The parameter connection generation submodule calculates the control direction combination between controlled parameters and establishes parameter connection paths based on the standard attribution distribution value, combines the parameter connection paths between multiple structural nodes, calculates the connection status of each group of parameters, and generates parameter connection combination coefficients. The indicator cross-calculation submodule calls the parameter connection combination coefficient, compares the cross-control content of parameters in each standard clause, identifies structural nodes with common control paths and records the associated clause number, analyzes the multi-directional control relationship of design standards in the graph structure, and obtains the indicator logic fusion density.

[0009] As a further aspect of the present invention, the process of establishing the attribution distribution between structural nodes and standard clauses specifically involves: after identifying the control attribution relationship of the standard items corresponding to the structural nodes, extracting a set of parameters related to the protective layer thickness, the foundation width, and the cross-sectional dimensions for each structural node; calculating the association ratio between the node parameters and the clause constraint content based on the frequency of occurrence and reference position of each parameter in the standard clause text; setting an attribution determination threshold based on the distribution range of the association ratio; and obtaining the attribution determination threshold by calculating the difference between the average constraint strength of the node parameters and the boundary constraint value of the same parameter item in the standard clause. During the attribution calculation process, the association ratio of each node parameter is determined to be higher than the attribution determination threshold. If it is higher, the target node is established with the corresponding standard clause, and the sequence number of the target connection in the attribution distribution is recorded. Based on the number of attribution connections between each node and the standard clause and the association ratio weight, the attribution distribution between the structural node and the standard clause is generated, and the standard attribution distribution value is obtained.

[0010] As a further aspect of the present invention, the task semantic attribution module includes: The functional distribution extraction submodule analyzes the functional content of structural nodes in the task description based on the logical fusion density of the indicators, retrieves the functional parameters associated with the nodes, including storage capacity, flow rate regulation and outflow rhythm, analyzes the distribution of each parameter in the structural nodes, identifies the functional affiliation of nodes in the task scenario, and obtains the node functional distribution coefficient. The parameter influence determination submodule calculates the influence direction of each structural parameter in the control path based on the node function distribution coefficient, compares the functional control differences of multiple structural nodes in the task path, identifies the dominant parameter and constructs the main control parameter path, and obtains the dominant parameter influence path value. The semantic tag mapping submodule calls the dominant parameter to influence the path value, identifies the task semantic keywords corresponding to the dominant parameter, establishes the index relationship between semantic tags and master nodes, constructs the graph task entry mapping and records the semantic tag binding information, and obtains the master semantic recognition tag.

[0011] As a further aspect of the present invention, the path filtering closure module includes: The path parameter extraction submodule analyzes the set of path parameters associated with the main control node in the map based on the main control semantic recognition tag, retrieves structural nodes involving channel slope, water storage section and cross-sectional width, numbers each path segment and records the parameter index to obtain the path structure parameter sequence; The boundary connectivity determination submodule determines the continuous connection relationship between structural segment parameters based on the path structure parameter sequence, determines the order and connectivity of boundary intersections in the parameter transmission path, calculates the path continuity matching degree value, compares the continuity matching degree value with the structural segment connection standard value, and obtains the path structure alignment index. The effective path filtering submodule identifies nodes with breaks and mismatched boundaries in the path based on the path structure alignment index and records the path number. It then removes path segments with missing synchronization control relationships, filters the set of effective paths, establishes a continuous verification chain, and obtains the path closure structure record.

[0012] As a further aspect of the present invention, the structural combination response module includes: The structural relationship extraction submodule analyzes the multi-structure combination relationship within a continuous path segment based on the path closure structure record, extracts structural nodes including dam body, diversion channel and water discharge facility, counts the combination distribution of structural nodes, identifies structural combination relationships, and obtains a structural node combination distribution table. The parameter linkage determination submodule calculates the corresponding ratio between the dam body inclination angle and the cross-sectional shape of the diversion channel according to the structural node combination distribution table, analyzes the influence direction of the inclination angle change on the geometric characteristics of the diversion cross-section, determines the control parameters of the channel cross-section change on the flow capacity of the water discharge facility, and obtains the parameter linkage response value. The response path generation submodule calls the parameter linkage response value to establish a response connection path between the diversion node and the discharge node, identifies the parameter transmission order between nodes in the path, analyzes the stability of parameter control transmission between nodes, identifies the structural combination that forms the linkage response and records the path information, and obtains the combined response coordination information.

[0013] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by constructing parameter control paths and combining them with the identification of multiple relationships between structural nodes, the logical linkage organization between structural parameters is realized. By utilizing the cross-relationship judgment mechanism between standard clauses, the constraint recognition capability of structural control paths is enhanced. By combining the index relationship of task semantic tags, the structural path screening has semantic guidance characteristics. The continuity judgment method of closed paths is adopted to optimize the structural matching accuracy of path screening. The response construction logic of structural combination relationships is used to improve the collaborative adaptability between multiple structures. A linkage path with continuity and logical dependence characteristics is established, thereby improving the logical integrity and response coordination of water conservancy design. Attached Figure Description

[0014] Figure 1 This is a system flowchart of the present invention; Figure 2 This is a flowchart of the parameter constraint construction module of the present invention; Figure 3A flowchart illustrating the design of the standard fusion module for this invention; Figure 4 This is a flowchart of the task semantic attribution module of the present invention; Figure 5 This is a flowchart of the path filtering closure module of the present invention; Figure 6 This is a flowchart of the structural combination response module of the present invention. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0016] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0017] Please see Figure 1 The knowledge graph-based hydraulic engineering design decision support system includes: The parameter constraint construction module calls the engineering survey data interface to analyze the engineering attributes of various survey data and their role paths in the design, calculates the linkage relationship between rock layer strength and lining thickness and establishes parameter control paths, calibrates the constraint transmission chain between structural nodes, and obtains the parameter logical dependent structure. The design standard fusion module utilizes the parameter logic dependency structure to analyze the control boundary between structural nodes and design parameters, retrieves the constraint clauses of structural parameters in the standard text, calculates the control combination between controlled parameters and establishes connection paths, identifies structural nodes with common control paths, and obtains the index logic fusion density. The task semantic attribution module analyzes the functional distribution of structural nodes in the task description based on the index logic fusion density, identifies the dominant parameter control path and matches task semantic keywords, establishes the index relationship between semantic tags and master control nodes, and obtains master control semantic recognition tags. The path filtering and closure module is based on the master semantic recognition label, analyzes the set of path parameters associated with the master node in the graph, calculates the continuous connection relationship between the parameters and filters the set of valid paths to obtain the path closure structure record; The structural combination response module analyzes the multi-structure combination relationship within a continuous path segment based on the path closure structure record, extracts structural nodes including dam body, diversion channel and water discharge facility, calculates the geometric correspondence and control ratio between structures, establishes response connection path and records path information, and obtains combined response coordination information.

[0018] The parameter logical dependency structure includes the head parameter control boundary, the seepage intensity linkage relationship, and the structural node dependency path. The indicator logical fusion density specifically includes the distribution of structural parameter control numbers, the standard clause control hierarchy, and the boundary intersection identifier between clauses. The master control semantic identification label includes the functional control label, the semantic master control path identifier, and the task entry mapping sequence. The path closure structure record specifically includes the structural path connection information, the boundary alignment matching order, and the path number filtering list. The combined response coordination information includes the structural node response sequence, the combined control ratio relationship, and the connection path index information.

[0019] Please see Figure 2 The parameter constraint construction module includes: The survey parameter identification submodule calls the engineering survey data interface to analyze the engineering attributes of various survey data and their role in the design, including water head height, permeability coefficient and rock strength. It determines the coupling trend between the variation range of permeability coefficient at the stratigraphic boundary and the rate of change of rock strength, establishes an engineering attribute matching table between hydrological permeability characteristics and rock mass structure response, and obtains the reference value of the survey parameter response relationship. Calling the engineering survey data interface, in analyzing the water head height... rice( The permeability coefficient is centimeters per second ( ), rock strata strength is Megapascal (MPa) After determining the engineering attributes, the specific execution process is as follows: for the geological boundary at the dam site, at a depth... Rice to Within the meter range, Permeability coefficient data were collected at intervals of meters to obtain a dataset. , , , , ]( Simultaneously, rock strength data at corresponding depths were collected to obtain a dataset. , , , , ]( ), calculate the array of rates of change of the permeability coefficient [ , , , ] and rock stratum strength change rate array [ , , , Determine the sign of the product of two rate-of-change arrays at corresponding positions. If the product is negative, it is denoted as "negative correlation coupling," such as in depth. Permeability coefficient change rate at a depth of meters With the rate of change of rock layer strength The product is This was determined to be a negatively correlated coupling, and this negatively correlated coupling trend was then linked to the corresponding hydrological permeability characteristics. ( "and rock mass structure response" ( The data is recorded together, and all collection points are traversed to complete the matching. Finally, an engineering attribute matching table is established, which contains four fields: "stratum location", "permeability coefficient value", "rock strength value", and "coupling trend". Specified engineering nodes are extracted from this table, such as the depth of the area where the lining structure is located. Data at a distance of meters was used to obtain a comparison value for the response relationship of survey parameters.

[0020] The control relationship derivation submodule analyzes the stability of the response of rock layer strength changes to lining thickness based on the comparison values ​​of the survey parameter response relationship, and calculates the boundary coupling state between rock layer strength, water head height, and permeability coefficient using the following formula: ; Calculate the constraint strength value of the linkage structure, determine the direction of response transmission between the linkage structures, and generate the linkage parameter action coefficient; in, This represents the constraint strength value of the linked structure. This is the normalized value of the rock stratum strength, obtained by reducing the original rock stratum strength data to its maximum value. The normalized value for the lining thickness is obtained by reducing the maximum value of the original lining thickness data. This is the normalized value of the permeability coefficient, obtained through reduction calculations using permeability test data. The normalized value of the water head height is obtained by reducing the data from the zoned water pressure monitoring. The ratio of the structural thickness boundary difference is calculated by dividing the difference between the maximum and minimum structural thickness by the average thickness. Based on the comparison values ​​of the response relationship of the survey parameters, the rock strata strength was analyzed. ( For the design lining thickness ( When responding to the action of ), the boundary coupling state between rock layer strength, hydraulic head, and permeability coefficient is calculated. The specific execution process is as follows: calling the formula Calculate the constraint strength value of the linked structure, where This represents the constraint strength value of the linked structure. This is the normalized value of the rock stratum strength. This is a normalized value for the lining thickness. This is the normalized value of the permeability coefficient. This is the normalized value of the water head height. The formula for calculating the ratio of structural thickness boundary differences is based on the logic that the numerator is calculated by multiplying the interaction between the rock strata and the lining. The radical term influenced by hydrogeological conditions The absolute value of the difference quantifies the degree of imbalance between structural constraints and hydrogeological constraints, with the denominator being... As a normalization factor, this formula comprehensively considers the dimensional variability of the structure itself and its normalized thickness. By defining the coupling relationship between soil and hydrological parameters, it quantifies the strength of constraint transfer between structures under the action of multiple factors. The original data of each parameter are shown in Table 1. Table 1 Original Data of Survey Parameters ; As shown in Table 1, the parameters were first normalized and calculated, and the normalized values ​​of the rock strata strength were obtained. Normalized value of lining thickness Normalized value of permeability coefficient Normalized value of water head Structural thickness boundary difference ratio Substitute the calculated parameter values ​​into the formula: ; The interconnected structural constraint strength value is a comprehensive parameter measuring the control and conduction strength between different engineering nodes in a hydraulic structural system under specific geological and hydrological conditions. A larger value indicates that a change in the parameter of one node in the interconnected structural pair will trigger a greater response from other related structural nodes; conversely, a smaller value indicates a limited impact. The core function of this parameter is to assess which locations in the structural system possess highly coupled and efficient critical paths, which can be used to construct more stable and responsive structural schemes. The results provide data support for subsequent path dependency construction and parameter optimization, serving as a preliminary quantitative basis for identifying strongly coupled node pairs in the constraint chain. The calculated interconnected structural constraint strength value... Compared with the preset intensity range, the intensity range is divided into: low influence zone ( ), moderate impact zone ), high-impact areas ), current calculation results Located in a low-impact zone, this result indicates that the constraint transmission between rock strength and lining thickness is weak. Based on this result, it is determined that the response transmission direction between the linked structures is dominated by hydrogeological conditions, ultimately generating the linkage parameter action coefficient.

[0021] The path dependency construction submodule analyzes the logical dependency order of the control path and establishes directional connections between nodes based on the linkage parameter action coefficient, records the parameter source information associated with the control path, identifies and marks the constraint transmission chain between structural nodes, and obtains the parameter logical dependency structure. Based on the linkage parameter coefficient is When analyzing the logical dependency sequence of the control path, the nodes involved in the calculation are first identified, namely "rock strength", "lining thickness", "permeability coefficient" and "water head height", based on the constraint strength value of the linkage structure. Located in the low impact zone The judgment of "rock stratum strength" indicates that its direct control over "lining thickness" is relatively weak, while the square root term in the formula calculation... numerical value Much larger than the product term numerical value Based on this, directional connections between nodes are established. Specifically, a directed edge is created from the "permeability coefficient" node to the "lining thickness" node, and then a directed edge is created from the "water head height" node to the "lining thickness" node. Simultaneously, since rock strength remains a fundamental condition, a secondary directed edge is created from "rock strength" to "lining thickness," and each edge is assigned a weight. This weight value is the interaction coefficient of the linkage parameter generated in the previous step. For example, the weight of the path from "permeability coefficient" to "lining thickness" is set to... Set the weight of the path from "rock strength" to "lining thickness" to 0.5. Next, the source information of the parameters associated with each control path is recorded. For example, the "permeability coefficient" comes from the field pressure water test data, and the "rock strength" comes from the borehole core test data. In this way, the core constraint transmission chain of "hydrological conditions → lining structure" is identified and calibrated, and the parameter logic dependent structure is obtained.

[0022] Please see Figure 3 The design standard integration module includes: The clause attribution determination submodule obtains the parameter logic dependency structure, analyzes the control boundary between structural nodes and design parameters, retrieves the constraint clauses of structural parameters in the standard text, including protective layer thickness, foundation width and cross-sectional dimensions, determines the control attribution relationship of the standard items corresponding to the structural nodes, identifies the parameter correspondence between structural nodes and design clauses, establishes the attribution distribution between structural nodes and standard clauses, and obtains the standard attribution distribution value. After obtaining the parameter logic dependency structure, when analyzing the control boundary between the "lining thickness" node and the design parameters, relevant texts of the hydraulic concrete structure design code are retrieved to locate constraint clauses involving "protective layer thickness," "foundation width," and "section dimensions," such as clause [example missing]. The clause specifies the minimum protective layer thickness. The basic width limit was specified, and then the control relationship between the "lining thickness" node and these standard items was determined. Specifically, the parameter set of the "lining thickness" node was extracted, including "thickness value," "concrete grade," and "reinforcement diameter," and these parameters were statistically analyzed in the clauses. and The frequency of occurrence and the location of citations in the text are used to calculate the "thickness value" of the clause. The correlation ratio is "Thickness value" and terms The correlation ratio is Next, an attribution determination threshold is set. This threshold is calculated by the difference between the average constraint strength of the node parameters and the boundary constraint value of the same parameter item in the standard clause. From the preceding steps, it is known that the average constraint strength of the "lining thickness" node is... The terms were obtained by consulting the regulations. The boundary constraint value regarding thickness is rice( After normalization, it becomes The threshold is then calculated as follows: The correlation ratio of node parameters Attribution threshold Comparison, because Then the "lining thickness" node will be linked to the clause. Establish a home link and record its index in the home distribution. Repeat this process, and finally generate the attribution distribution between structural nodes and standard clauses based on the number of attribution connections and the association ratio weight, to obtain the standard attribution distribution value.

[0023] The parameter connection generation submodule calculates the control direction combination between controlled parameters and establishes parameter connection paths based on the standard attribution distribution value. It combines the parameter connection paths between multiple structural nodes, calculates the connection status of each group of parameters, and generates parameter connection combination coefficients. Based on the standard attribution distribution value, when calculating the combination of control directions among controlled parameters, the "lining thickness" node was identified as belonging to the relevant clause. The "base width" node belongs to the clause. Text analysis revealed the terms With Terms All of them cited the clauses regarding "permeability grade". Based on this, a parameter connection path is established starting from the "lining thickness", passing through the "seepage resistance grade" node, and finally reaching the "foundation width" node. At the same time, the attribute of another structural node, "dam slope", to the clause is analyzed. This clause and the clause Both are constrained by the "foundation bearing capacity" parameter. Therefore, another connection path is established from "dam slope" to "foundation width". These two paths are combined to form a parameter connection path combination containing three nodes: "lining thickness", "foundation width", and "dam slope". The connection condition of this parameter set is then calculated. The connection tightness is defined as the number of shared upstream constraint nodes. In this example, "lining thickness" and "foundation width" do not share upstream nodes, while "dam slope" and "foundation width" share the "foundation bearing capacity" node. Therefore, its connection tightness is... Finally, the connection density values ​​of all path combinations are statistically analyzed to generate parameter connection combination coefficients.

[0024] The indicator cross-calculation submodule calls the parameter connection combination coefficient, compares the cross-control content of the parameters in each standard clause, identifies structural nodes with common control paths and records the associated clause numbers, analyzes the multi-directional control relationship of the design standard in the graph structure, and obtains the indicator logical fusion density. When comparing the overlap of parameter control content in each standard clause using the parameter connection combination coefficient, the parameter connection path generated in the previous module is extracted, such as the path "lining thickness → impermeability grade → foundation width", and its associated clause number is recorded. Terms and Conditions and terms Simultaneously, another path is extracted: "Rock stratum strength → Foundation bearing capacity → Foundation width," and its associated clauses are clauses. Terms and Conditions and terms A comparison revealed that the "basic width" node at the end of both paths is associated with the clause. Therefore, the "Basic Width" node is identified as a structural node with a common control path, and its associated common clause number is recorded. and the upstream terms set { , Subsequently, the multi-directional control relationships of the design standards in the diagram structure were analyzed. It was found that the "foundation width" node received control inputs from two different directions: one from the hydraulic requirement of "permeability grade," and the other from the geotechnical requirement of "foundation bearing capacity." The number of such multi-directional control nodes was divided by the total number of all structural nodes in the diagram to calculate the value. Obtain the density of logical fusion of indicators.

[0025] Please see Figure 4 The task semantic attribution module includes: The functional distribution extraction submodule analyzes the functional content of structural nodes in the task description based on the index logic fusion density, retrieves the functional parameters associated with the nodes, including storage capacity, flow rate regulation and outflow rhythm, analyzes the distribution of each parameter in the structural nodes, identifies the functional affiliation of nodes in the task scenario, and obtains the node functional distribution coefficient. Based on the index logic fusion density is When analyzing the functional content of the "spillage facility" structural node in the task description "emergency flood discharge," the functional parameters associated with the "spillage facility" node were retrieved, and "gate opening," "weir crest elevation," and "channel roughness" were extracted. Then, the distribution of each parameter in the structural node was analyzed. Through design document analysis, the direct correlation between "gate opening" and the "emergency flood discharge" task was found to be... The "weir crest elevation" is primarily related to the "normal water storage" task, with a correlation degree of [missing information]. The correlation between "channel roughness" and the "long-term water conveyance efficiency" task is [correlation degree]. Based on this correlation distribution, the "water discharge facility" node is classified as a "direct control area" in the "emergency flood discharge" scenario and an "indirect influence area" in the "normal water storage" scenario. Finally, the correlation values ​​of each functional parameter are determined... , , After normalization, the result is calculated as follows: , , [, obtain the node function distribution coefficient.]

[0026] The parameter influence determination submodule calculates the influence direction of each structural parameter in the control path based on the node function distribution coefficient, compares the functional control differences of multiple structural nodes in the task path, identifies the dominant parameter and constructs the main control parameter path, and obtains the influence path value of the dominant parameter. Based on the node functional distribution coefficient , , When calculating the influence direction of each structural parameter in the control path, the "gate opening" parameter (with a coefficient of ) is determined. The influence direction of the opening is positive, meaning that increasing the opening can increase the flood discharge, while the "channel roughness" parameter (coefficient is...) The influence direction is negative, meaning that increasing the roughness will reduce the flood discharge. Next, comparing the functional control differences between the "flood discharge facility" node and the "upstream reservoir" node in the "emergency flood discharge" task path, it was found that the control coefficient of the "flood discharge facility" is negative. Much greater than the control coefficient of the "upstream reservoir" Based on this, "gate opening" is identified as the dominant parameter, and a path is constructed from the "operation command" node, pointing to the "gate opening" node, and then to the "flood discharge" node. This path serves as the main control parameter path. The node function distribution coefficients of each node along this path are weighted and summed to calculate... This yields the dominant parameters that influence the path value.

[0027] The semantic tag mapping submodule calls the dominant parameter to influence the path value, identifies the task semantic keywords corresponding to the dominant parameter, establishes the index relationship between semantic tags and the master node, constructs the graph task entry mapping and records the semantic tag binding information, and obtains the master semantic recognition tag. Calling the dominant parameter affects the path value When identifying the task semantic keywords corresponding to the dominant parameter "gate opening", the task description "to bring the downstream river level to..." is used. From the phrase "water level drops from warning level to safe level within hours," the keywords "water level decrease" and "rapidly" are extracted, and the influence path value of the dominant parameter is determined. The comparison is made with a preset semantic association threshold, which is based on the statistical average of the influence values ​​of the main control parameters in similar historical engineering tasks. with standard deviation The calculation is based on the mean plus one standard deviation, i.e. ,because The system determines that there is a strong correlation between "gate opening" and the keywords "rapid" and "water level reduction". It then establishes an index relationship between the semantic tag "rapid water level regulation" and the main control node "gate opening". This mapping relationship is stored in the database, a graph task entry mapping is constructed, and the binding information of the semantic tag is recorded, including the creation time, associated task number and impact path value, to obtain the main control semantic recognition tag.

[0028] Please see Figure 5 The path filtering closure module includes: The path parameter extraction submodule analyzes the set of path parameters associated with the master control node in the map based on the master control semantic recognition tag, retrieves the structural nodes involving channel slope, storage section and cross-sectional width, numbers each path segment and records the parameter index, and obtains the path structure parameter sequence. Based on the main control semantic recognition tag "rapid water level regulation", when analyzing the set of path parameters associated with the main control node "gate opening" in the analysis map, a complete physical path was retrieved. This path involves three structural nodes in sequence: "upstream water diversion channel", "gate control section", and "downstream spillway". Further retrieval of the design parameters of these three nodes yielded the parameter value related to "channel slope". The parameter value related to the "storage storage section" is length. rice( The parameter values ​​related to "section width" are respectively at the three nodes. rice( ), rice( )and rice( Number the two consecutive path segments of the path. The section is from the "upstream water diversion channel" to the "gate control section". The path is divided into "gate control section" and "downstream spillway", and the parameter index of each path segment is recorded to obtain the path structure parameter sequence.

[0029] The boundary connectivity determination submodule determines the continuous connection relationship between structural segment parameters based on the path structure parameter sequence, and judges the order and connectivity of boundary intersections in the parameter transmission path using the following formula: ; Calculate the path continuity matching degree value, compare the continuity matching degree value with the structural segment connection standard value, and obtain the path structure alignment index; in, This is the path continuity matching value, used to measure the sequential coherence of parameter connections between path structure segments. The number of path structure segments is obtained by counting the number of connections between structure nodes in each path. This is the index number of the current path structure segment, used to index the first... Parameters in the segment path This is the index number of the next segment after the current segment, used to construct the parameter difference between adjacent segments. For the first The normalized value of the segment path length is obtained by extracting the segment length and dividing it by the maximum segment length within the path. For the first The normalized value of the cross-sectional width difference of the segment structure path is calculated by the first... Section and the The difference in segment width is obtained by dividing by the maximum difference in width across the entire path. For the first The normalized value of the terrain variation range in the area where the route segment is located is obtained by comparing and normalizing the elevation differences between the start and end points of the nodes. For the first The normalized value of the density of water storage sections is obtained by statistically analyzing the number of water storage facilities per unit path length and then normalizing it. For the first The normalized value of the logical node code of a segment is obtained by normalizing the node logical sequence number. For the first The normalized value of the logical node encoding of the segment, and Similarly, it is obtained through normalized logical numbering; Based on the path structure parameter sequence, when determining the continuous connection relationship between structure segment parameters, the formula is called. Calculate the path continuity matching degree value, where This represents the path continuity matching degree. This represents the number of path structure segments. This is the index number of the current path segment. For the first Normalized value of segment structure path length. For the first Normalized value of the cross-sectional width difference of the segment structure path. For the first The normalized value of the terrain variation range in the area where the route segment is located. For the first The normalized value of the density of the storage section. For the first The normalized value of the logical node encoding of the segment; the calculation logic of this formula lies in the numerator term. The degree of geometric abrupt change in the path's length and width is quantified, and the square root term in the denominator... This represents the buffering capacity of the terrain and water storage facilities on the water flow; the absolute value term. This represents the continuity of the logical order. The entire fraction evaluates the inconsistency of the connection between each segment. Finally, the overall degree of mismatch of the entire path is obtained by summing and averaging. The formula quantifies the physical and logical coherence of the path by integrating geometric, geological and logical parameters. The original data of the path segments are shown in Table 2. Table 2 Path Structure Segment Parameter Table ; As shown in Table 2, in order to substitute the physical dimensional data in Table 2 into the formula To perform dimensionless calculations, it is necessary to first establish a normalized baseline value based on the full path data and establish a mapping relationship between the original parameters and formula symbols. The specific extraction and definition process is as follows: First, extract the normalized baseline value (denominator) of the entire path: Traverse all path segment data in Table 2 and identify the maximum segment length of the entire path. for (Taken from section 2); Calculate the absolute value of the difference in cross-sectional width for each section ( , Extract the maximum width difference for Extract the overall elevation difference along the path. Starting point and the end point The difference, that is ; Calculate the storage density of each section (section 1 is...) Section 2 is Extract the maximum storage density. for Extract the maximum logical code. for (Taken from the next logical code).

[0030] Second, define the computational mapping (numerator) between formula symbols and the data in Table 2: In the formula Corresponding to "Path Segment Length" in Table 2 "and The ratio; in the formula The absolute value of the difference in width between the starting and ending sections corresponds to the value in Table 2. The ratio; in the formula The absolute value of the starting / ending elevation difference corresponds to the value in Table 2. The ratio; in the formula Corresponding to the "Number of Storage and Regulation Facilities" in Table 2 Divide by length The obtained density value and The ratio; in the formula Corresponding to "Logical Encoding" in Table 2 The ratio; Number of path segments First, the parameters are calculated and normalized to determine the maximum segment length of the entire path. ( ), maximum width difference of the entire path ( Maximum elevation difference along the entire path ( Maximum storage density along the entire path Maximum logical encoding of the entire path For segment 1 ( ): , , , , , For segment 2 ( ): , , , , , Substitute the parameter values ​​into the formula: ; ; ; The path continuity matching value is an indicator used to measure the stability of parameter continuous transmission in a structural path. Essentially, it assesses whether the connection and coherence between structural nodes in the graph path conforms to the design logic. A smaller value indicates a more coordinated match between structural segments in terms of structural parameters, logical relationships, and physical conditions, resulting in better path continuity and suitability for closed path identification and effective path selection. Conversely, a larger value indicates structural abrupt changes, logical jumps, or sudden drops in regulation performance, which can easily lead to path closure failure or response chain interruption. This parameter serves as a crucial threshold for determining path validity, providing a structural closure basis for subsequent structural combination response and task semantic mapping. A structural segment connection standard value of 0.3 is set; this standard value is obtained by analyzing similar paths from 10 successfully operating water conservancy projects. The value was calculated using the 80th percentile of the result. The calculated result of 0.433 was compared to the standard value of 0.3. The path structure alignment index was found to be "not satisfied".

[0031] The effective path filtering submodule identifies broken and mismatched nodes in the path based on the path structure alignment index and records the path number. It removes path segments with missing synchronization control relationships, filters the effective path set, establishes a continuous verification chain, and obtains the path closure structure record. Based on the path structure alignment index being "not satisfied" and the path continuity matching value being 0.433, when identifying nodes with breaks and boundary mismatches in the path, backtracking the calculation process revealed that the calculation item for the second path segment... Its value is much higher than 0.205 of the first path segment. Based on this, it is determined that there is a significant boundary mismatch at the connection between the "gate control section" and the "downstream spillway". The path number "Path-001" and the mismatch node "downstream spillway" are recorded. Then, the path is removed from the set of valid paths. Next, the system continues to analyze the next candidate path and repeats the boundary connectivity determination process until all paths are analyzed. Paths with a continuous matching degree value of less than 0.3 are selected. A continuous verification chain is established for these selected paths to obtain the path closure structure record.

[0032] Please see Figure 6 The structural combination response module includes: The structural relationship extraction submodule analyzes the multi-structure combination relationship within a continuous path segment based on the path closure structure record, extracts structural nodes including dam body, diversion channel and water discharge facility, counts the combination distribution of structural nodes, identifies structural combination relationship, and obtains structural node combination distribution table; Based on the path closure structure record, when analyzing the multi-structure combination relationship within the continuous path segment of a certain effective path "Path-002", the structural nodes arranged sequentially on this path are extracted, namely "dam body", "diversion channel" and "spillage facility". The combination distribution of these three nodes is statistically analyzed, revealing that they exist in all... The same appeared in all the valid paths Therefore, the "dam body-diversion channel-discharge facility" is identified as a high-frequency structural combination, and this combination is correlated with its frequency of occurrence. Record all valid paths and all node combinations together, and finally generate a structured node combination distribution table containing fields such as "nodes within the combination", "frequency of occurrence of the combination", and "path number".

[0033] The parameter linkage judgment submodule calculates the corresponding ratio between the dam body inclination angle and the cross-sectional shape of the diversion channel based on the structural node combination distribution table, analyzes the influence direction of the inclination angle change on the geometric characteristics of the diversion channel, determines the control parameters of the channel cross-sectional change on the flow capacity of the water discharge facility, and obtains the parameter linkage response value. Based on the structural node combination distribution table, when calculating the corresponding ratio between the dam body inclination angle and the diversion channel cross-sectional shape in the "dam body-diversion channel" combination, the following parameters are extracted: A set of successful case data, in which the dam body inclination angles are respectively [ , , , , The corresponding cross-sectional shapes of the flow guiding channels (expressed as width-to-depth ratio) are as follows: , , , , ] Calculate the covariance of the two sets of data. The standard deviation of the dam body inclination angle is The standard deviation of the width-to-depth ratio is The correlation coefficient was obtained as Based on this, it is determined that as the dam inclination angle increases, the width-to-depth ratio of the diversion channel also increases, with the influence direction being positive. Next, it is determined that the control parameter for the flow capacity of the spillway facility based on the change in the width-to-depth ratio of the channel cross-section is the "inlet velocity." The calculation is performed when the width-to-depth ratio changes from... Increase to At that time, the inlet flow rate was from ( Reduced to ( Finally, this linkage relationship is quantified to obtain the parameter linkage response value.

[0034] The response path generation submodule calls the parameter linkage response value, establishes the response connection path between the diversion node and the discharge node, identifies the parameter transmission order between nodes in the path, analyzes the stability of parameter control transmission between nodes, identifies the structural combination that forms the linkage response and records the path information, and obtains the combined response coordination information. When establishing the response connection path between the diversion node and the discharge node by calling the parameter linkage response value, based on the linkage relationship between the "diversion channel width-to-depth ratio" and the "discharge facility inlet velocity" determined by the previous module, a directed edge is created from the "diversion channel" node to the "discharge facility" node, and its response type is marked as "negative correlation". Then, the parameter transmission order between nodes in the path is identified as follows: the engineer adjusts the "dam inclination angle" parameter, this change is transmitted to the "diversion channel width-to-depth ratio" parameter through the "dam-diversion channel" combination relationship, and then to the "discharge facility inlet velocity" parameter through the "diversion-discharge" linkage relationship. Next, the stability of parameter control transmission between nodes is analyzed, and the transfer function from "dam inclination angle" to "inlet velocity" is calculated based on historical data. Its first derivative is within the design range. The fluctuation is less than The system was determined to be a stable transmission. Finally, the structural combination of "dam body-diversion channel-discharge facility" was identified as a structural combination that forms a linkage response, and its complete response path information was recorded to obtain the combined response coordination information.

[0035] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A water conservancy design decision support system based on a knowledge graph, characterized in that, The system comprises: The parameter constraint construction module calls the engineering survey data interface, analyzes the engineering properties and role paths in the design of various survey data, calculates the linkage relationship between rock strength and lining thickness and establishes a parameter control path, calibrates the constraint transmission chain between structure nodes, and obtains a parameter logical attachment structure; The design standard fusion module uses the parameter logical attachment structure to analyze the control boundaries between structure nodes and design parameters, retrieves constraint clauses of structure parameters in standard texts, calculates control combinations between controlled parameters and establishes connection paths, identifies structure nodes with common control paths, and obtains index logical fusion density; The task semantic attribution module, based on the index logical fusion density, analyzes the functional distribution of structure nodes in task descriptions, identifies dominant parameter control paths and matches task semantic keywords, establishes an index relationship between semantic labels and master nodes, and obtains master semantic identification labels; The path screening and closing module, based on the master semantic identification labels, analyzes the path parameter set associated with the master nodes in the atlas, calculates the continuous connection relationship between parameters and screens the effective path set, and obtains path closure structure records. 2.The knowledge graph-based water conservancy design decision support system according to claim 1, characterized in that, The parameter logical attachment structure comprises water head parameter control boundaries, seepage strength linkage relationships and structure node attachment paths, the index logical fusion density is specifically structure parameter control number distribution, standard clause control level and clause intersection identification, the master semantic identification label comprises function control label, semantic master path identification and task entry mapping sequence, and the path closure structure record is specifically structure path connection information, boundary alignment matching order and path number screening list. 3.The knowledge graph-based water conservancy design decision support system according to claim 1, characterized in that, The parameter constraint construction module comprises: The survey parameter identification submodule calls the engineering survey data interface, analyzes the engineering properties and role paths in the design of various survey data, including water head height, permeability coefficient and rock strength, judges the coupling trend of the change interval of the permeability coefficient at the stratum boundary and the change rate of the rock strength, establishes an engineering property matching table of hydrological seepage characteristics and rock mass structure response, and obtains survey parameter response relationship comparison values; The control relationship derivation submodule, according to the survey parameter response relationship comparison values, analyzes the stability of the response effect of rock strength change on lining thickness, calculates the boundary coupling state among rock strength, water head height and permeability coefficient, uses the formula: ； calculates the linkage structure constraint strength value, judges the response transmission direction between linkage structures, generates linkage parameter action coefficients; wherein, is a linkage structure constraint strength value, is a normalized value of rock strength, is a normalized value of lining thickness, is a normalized value of permeability coefficient, is a normalized value of water head height, is a structure thickness boundary difference ratio value; The path attachment construction submodule, based on the linkage parameter action coefficients, analyzes the logical attachment order of the control path and establishes the directional connection between nodes, records the parameter source information associated with the control path, identifies and calibrates the constraint transmission chain between structure nodes, and obtains a parameter logical attachment structure.

4. The knowledge graph-based hydraulic design decision support system according to claim 3, wherein, The design standard fusion module comprises: The clause attribution determining submodule obtains the parameter logical dependency structure, analyzes the control boundary between the structure node and the design parameter, retrieves the constraint clauses of the structure parameter in the standard text, including the thickness of the protective layer, the width of the foundation and the section size, determines the control attribution relationship of the standard item corresponding to the structure node, identifies the parameter corresponding mode between the structure node and the design clause, establishes the attribution distribution between the structure node and the standard clause, and obtains the standard attribution distribution value; The parameter connection generating submodule calculates the control direction combination of the controlled parameters based on the standard attribution distribution value, establishes the parameter connection path, combines the parameter connection paths among multiple structure nodes, calculates the connection condition of each group of parameters, and generates the parameter connection combination coefficient; The index intersection calculating submodule calls the parameter connection combination coefficient, compares the intersection condition of the parameter control content in each standard clause, identifies the structure nodes with the common control path and records the associated clause number, analyzes the multidirectional control relationship of the design standard in the graph structure, and obtains the index logical fusion density.

5. The knowledge graph-based hydraulic design decision support system according to claim 4, wherein, The process of establishing the attribution distribution between the structure node and the standard clause specifically comprises: after identifying the control attribution relationship of the standard item corresponding to the structure node, extracting the parameter set related to the thickness of the protective layer, the width of the foundation and the section size for each structure node, calculating the association ratio of the node parameter and the clause constraint content according to the appearance frequency and the reference position of each parameter in the standard clause text, setting the attribution determination threshold value according to the distribution range of the association ratio, and obtaining the attribution determination threshold value by calculating the difference between the average constraint strength of the node parameter and the boundary constraint value of the same parameter item in the standard clause; In the attribution calculation process, whether the association ratio of each node parameter exceeds the attribution determination threshold value is judged, if yes, the target node and the corresponding standard clause are connected in attribution, the serial number information of the target connection in the attribution distribution is recorded, the attribution distribution between the structure node and the standard clause is generated according to the number of attribution connections and the association ratio weight between each node and the standard clause, and the standard attribution distribution value is obtained. 6.The knowledge graph-based hydraulic design decision support system according to claim 4, characterized in that, The task semantic attribution module comprises: The function distribution extracting submodule analyzes the function content of the structure node in the task description based on the index logical fusion density, retrieves the function parameter content associated with the node, including the storage capacity, the flow rate regulation and the outflow rhythm, analyzes the distribution of each parameter in the structure node, identifies the function attribution partition of the node in the task scene, and obtains the node function distribution coefficient; The parameter influence determining submodule calculates the influence direction of each structure parameter in the control path according to the node function distribution coefficient, compares the function control difference of multiple structure nodes in the task path, identifies the dominant parameter and constructs the master parameter path, and obtains the dominant parameter influence path value; The semantic label mapping submodule calls the dominant parameter influence path value, identifies the task semantic keywords corresponding to the dominant parameter, establishes the index relationship between the semantic label and the master node, constructs the graph task entrance mapping and records the semantic label binding information, and obtains the master semantic recognition label.

7. The knowledge graph-based hydraulic design decision support system according to claim 6, wherein, The path screening and closing module comprises: The path parameter extraction submodule analyzes a path parameter set associated with the master node in a graph based on the master semantic identification tag, retrieves structure nodes related to channel slope, regulation and storage section, and cross section width, numbers each path segment and records parameter index, and obtains a path structure parameter sequence; The boundary connectivity determination submodule determines the continuous connection relationship between structure segment parameters based on the path structure parameter sequence, determines the order and connectivity of boundary intersections in the parameter transmission path, calculates the path continuous matching degree value, compares the continuous matching degree value with the structure segment connection standard value, and obtains the path structure alignment index; The effective path screening submodule identifies nodes with broken paths and unmatched boundaries in the path and records path numbers based on the path structure alignment index, eliminates path segments that lack synchronous control relationship, screens an effective path set, establishes a continuity verification chain, and obtains path closure structure records. 8.The knowledge graph based hydraulic design decision support system according to claim 1, wherein, The system further comprises: The structure combination response module analyzes the multi-structure combination relationship in the continuous path segment based on the path closure structure records, extracts structure nodes including dam body, diversion channel, and discharge facility, calculates the geometric correspondence and control proportion between structures, establishes a response connection path and records path information, and obtains combination response coordination information; The combination response coordination information includes structure node response sequence, combination control proportion relationship, and connection path index information.

9. The knowledge graph-based hydraulic design decision support system according to claim 8, wherein, The structure combination response module comprises: The structure relationship extraction submodule analyzes the multi-structure combination relationship in the continuous path segment based on the path closure structure records, extracts structure nodes including dam body, diversion channel, and discharge facility, counts the combination distribution of structure nodes, identifies structure combination relationship, and obtains a structure node combination distribution table; The parameter linkage determination submodule calculates the corresponding proportion between dam body inclination and diversion channel cross section shape based on the structure node combination distribution table, analyzes the influence direction of inclination change on diversion cross section geometric characteristics, determines the control parameter of channel cross section change on discharge facility flow capacity, and obtains parameter linkage response value; The response path generation submodule calls the parameter linkage response value, establishes a response connection path between diversion nodes and discharge nodes, identifies the parameter transmission order between nodes in the path, analyzes the stability of parameter control transmission between nodes, identifies structure combinations forming linkage response and records path information, and obtains combination response coordination information.

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