30 results about "Structure type" patented technology

The invention discloses a medium and small span bridge modeling method based on an adaptive rule and a parameterized template, which comprises the following steps: splitting a bridge structure into a standard component and an adaptive component according to the type of the bridge structure, establishing a parameterized model library of the standard component, and setting parameter linkage and constraint among the components in combination with route topographic data, and generating a standard component model, on the basis of the standard component model, automatically calculating and fitting the physical dimension of the component at the missing part, and refining to generate a self-adaptive component model, thereby completing full-bridge three-dimensional high-precision modeling. By means of the mode, the defect that in the traditional parametric modeling process, parameter input and output are mainly manual work is overcome, full-process parametric driving design of engineering data-component design-model assembly is achieved, and the technical problem that under a complex curve route, the modeling precision of a small and medium-span bridge parametric model base is insufficient is solved; the linkage between bridge parametric modeling components is improved, input of repeated parameters in the model is effectively reduced, and the modeling efficiency is improved.

The embodiment of the invention discloses a data processing method, device and equipment, and the method comprises the steps: obtaining a plurality of different structural text data which can be decomposed into a plurality of different levels or substructures with position dependence; performing structural disassembly processing on each piece of structural text data to obtain a structural node corresponding to each piece of structural text data, and performing word segmentation processing on each structural node; for each segmented word, determining each segmented word and a corresponding context neighborhood, and further respectively determining semantic significance information between each segmented word and the corresponding context neighborhood, local contrast loss information corresponding to each segmented word and a boundary sparsification factor corresponding to each segmented word; further determining semantic anomaly significance information corresponding to each segmented word; and determining generalizable white list information and / or abnormal structural text data from a plurality of different structural text data based on the determined semantic anomaly significance information.

The invention discloses a financial question analysis method and device based on a large language model, equipment and a medium, and relates to the technical field of natural language processing, and the method comprises the steps: retrieving a target sub-graph corresponding to a to-be-analyzed financial question from a knowledge graph, and carrying out the topology analysis of the target sub-graph, so as to obtain a structural representation vector; determining a graph structure type by using the structure representation vector, and determining a cue word template based on the graph structure type; determining priorities corresponding to the nodes on the basis of semantic relevancy and time relevancy between the nodes in the target sub-graph and the financial problem to be analyzed and PageRank scores of the nodes, sorting and recombining the nodes according to the priorities to obtain a target logic flow, and filling the cue word template by using the target logic flow to obtain a cue word template; obtaining a target prompt word; and inputting the target cue word into the large language model so as to generate an analysis result. A structural representation vector is obtained through topology analysis, and the problem of confusion of context organization of a generated result is solved.

The application provides a method and device for structuring thread steel data based on a laser point cloud, and the method comprises the following steps: obtaining a three-dimensional structure point cloud of thread steel; unfolding the three-dimensional structure point cloud to obtain an unfolded point cloud; generating an unfolded depth map of thread steel through the unfolded point cloud; identifying the unfolded depth map to obtain the positions of different structures in the unfolded depth map; and obtaining a plurality of groups of point clouds from the three-dimensional structure point cloud based on the positions of different structures in the unfolded depth map, wherein the structure types of each group of point clouds are the same. The technical problem of poor accuracy of structured data caused by manual measurement of thread steel data in the prior art is solved.

The invention relates to the technical field of railway signal safety control, and provides an interlocking product data analysis method, system and equipment, and the method comprises the steps: analyzing program language data in interlocking software, and obtaining a structural body type definition and a structural body variable; a multi-way tree is constructed according to the structural body type definition, and a multi-way tree model is optimized through node replacement; the optimized multi-way tree is adopted to carry out assignment analysis on the structural body variables, and structural body variable values are obtained; and verifying the obtained structural body variable value and input data, and outputting a verification result. According to the interlocking product data analysis method, system and equipment, structured analysis of interlocking program language data is realized by constructing the multi-way tree model and carrying out node replacement optimization, a complex data structure is efficiently processed, unanalyzed nodes are ensured to be correctly supplemented through a queue traversal and type replacement mechanism, and the data analysis efficiency is improved. And the integrity and accuracy of data analysis are improved.

The invention relates to a magnetic thrust assembly design method and device and a magnetic thrust prediction method. The method comprises the steps that the structure type and constraint conditions of the magnetic thrust assembly are obtained, and the structure type corresponds to at least one basic structure; constructing a structure parameter condition according to the structure type; and determining at least one group of target parameters of the magnetic thrust assembly based on an optimization algorithm and a thrust prediction model according to the structure parameter condition and the constraint condition. According to the method, automatic design of the magnetic thrust assembly is carried out through the optimization algorithm and the pre-trained thrust prediction model, so that the design time of the magnetic thrust assembly is shortened, and the design cost of the magnetic thrust assembly is further reduced.

A system may attempt to classify, according to field types, labels fields used by structures in instances of different log data source types, which use different structure types and different path information to access the structures of those structure types within the instances. Each of the structures includes at least one of the label fields and at least one data field associated with that label field. The system may store a result that includes the path information to access the structures and mappings of at least some of the field labels to the field types. The system may determine a field type involved in a system level query, and then generate a set of query graphs based on the field type and the result. The system may generate a set of instance level queries for a set of the instances according to the set of query graphs.

The invention provides a templated format conversion method and system for hierarchical metadata, and relates to the technical field of data format conversion, and the method comprises the following steps: receiving a metadata file in a JSON format; the method comprises the following steps of: recursively analyzing a metadata file in a JSON format, verifying fields of the metadata file in a manner of combining a structure tree model with a category label suspension mark, if the fields have an STRUCT structure body type, traversing all fields in an STRUCT structure body to generate a tree-shaped data structure, and if the fields have an ARRAY array type, traversing all fields in an ARRAY array to generate a tree-shaped data structure; if the field is of a basic field type, traversing the basic field to generate a set type data structure, and if the field is of a basic field type, traversing the basic field to generate a specific type data structure; the XML format file is generated according to different types of data structures, and the complete hierarchical relation of the original JSON format metadata file is reserved. The problems that in the prior art, unique complex types of metadata cannot be automatically processed, and nested structure output is not supported are solved.

The application discloses a kind of elastic modulus prediction calculation methods under the multiscale of ultra-high performance concrete, the prediction calculation method includes (1) according to material composition and representative volume element (RVE) size, the structure type of determining solution object;(2) according to the structure type of solution object, RVE unit internal component is divided into matrix phase and inclusion phase;(3) according to the volume content of matrix phase, elastic parameter and the morphology of inclusion phase, elastic parameter, volume content, the local strain concentration tensor of all inclusion phase is calculated;(4) according to the local strain concentration tensor of all inclusion phase, the elastic parameter of RVE is calculated using mean field theory.Compared with conventional test methods such as empirical formula method, finite element calculation method, this method is not only more suitable for a variety of doped ultra-high performance concrete composite materials, but also can improve the calculation efficiency of concrete elastic parameters under different scales.

The invention relates to the technical field of steel structure drawing, in particular to a modeling method and device for a frame structure and a storage medium. The method comprises the steps that a modeling environment is created, the modeling environment comprises a plurality of free datum lines, and the free datum lines are staggered to obtain a plurality of modeling nodes; in response to the modeling operation, a frame structure type selected by a user and a plurality of target modeling nodes are obtained, and the frame structure type comprises a first-class frame structure and a second-class frame structure; based on the modeling parameters of the first-class frame structure, generating the first-class frame structure at the plurality of target modeling nodes; and / or generating the second-class frame structure between the adjacent target modeling nodes based on the modeling parameters of the second-class frame structure. While the modeling speed of the frame structure is increased, the accuracy of the modeling position of the frame structure is considered, and the batch modeling efficiency of the frame structure is improved.

This application discloses a method and electronic device for rendering and displaying model output data, including: receiving and parsing current data from a structured document streamed by an artificial intelligence (AI) language model to predict the structure type corresponding to a target tag included in the current data; the structure type includes: a structure type defined for the main content in the structured document; if the markup language corresponding to the predicted structure type consists of multiple tags existing in pairs or groups, and the target tag belongs to a tag pair or group, then based on the other tags in the tag pair or group, temporary tags are added to the current data and provided to the rendering engine, so that the rendering engine can perform data rendering when it perceives the complete tags corresponding to the structure type in advance. Through this application embodiment, structural anomalies or structural mutations can be avoided or reduced.

The application discloses a preparation method of a high-plasticity hierarchical structure SnO2 reinforced modified silver-based composite material. The application quantitatively and stably prepares SnO2 reinforced phase powder with a sandwiched three-layer structure type and a hierarchical structure characteristic by using a crystal type transformation regulation and control new strategy, and combines a cumulative cold drawing process to prepare a new type of Ag / SnO2 composite material with high plasticity, solves the industry bottleneck problems of poor plasticity and high processing difficulty of a traditional Ag / SnO2 composite material, and promotes the industrialization process of the Ag / SnO2 composite material.

The embodiment of the invention provides a data processing method, device and equipment. The method comprises the following steps: generating to-be-written data; determining a structure type of the to-be-written data, wherein the structure type is a structured type or an unstructured type; under the condition that the structure type is an unstructured type, performing multi-modal feature analysis on the to-be-written data, and determining feature information of the to-be-written data; the feature information is used for indicating the content attribute, the security level and the use scene of the to-be-written data; and storing the to-be-written data in a target node according to the feature information, the target node being a computing node in a data cluster managed by the server. The data processing mode provided by the invention is suitable for read-write operation of the unstructured data.

The invention provides a binary organization automatic modeling method based on neper, and relates to the technical field of material science numerical simulation modeling, and the method comprises the steps: building a Thiessen polygon geometric model based on neper software, and obtaining a geo file corresponding to the geometric model; and on the basis of each crystal grain, the normal vector of the shared crystal face of each crystal grain and a plurality of adjacent crystal grains and the serial numbers of the crystal grains in the geo file, identifying the structure type of each crystal grain, so that the material parameters of the crystal grains are endowed according to the structure type of each crystal grain, and a double-state structure model is obtained. According to the method, the structure type of each crystal grain is automatically identified according to the serial number characteristic of each crystal grain in the geo file generated on the basis of the binary structure geometric model established by the neper software and the characteristic of the normal vector of the shared crystal face between the crystal grain and the adjacent crystal grain, so that the corresponding material parameter is given to each crystal grain; full-automatic modeling of the double-state organization is achieved, the modeling period is remarkably shortened, and the simulation efficiency is improved.

The invention provides a structure prediction model suitable for alloy steel and an establishment method and application thereof, and the establishment method comprises the following steps: S1, obtaining component and structure type data of a plurality of steel grades covered by a component range, and calculating the statistical characteristics of each element by taking the mass fraction of the alloy element as a characteristic variable; s2, data processing is conducted, a decision boundary is obtained, and structure types are divided into single-phase austenite, austenite and ferrite or martensite, ferrite and / or martensite; and S3, predicting the model: performing dimensionality reduction on the obtained data by adopting the linear discriminant analysis in the step S2, combining softmax regression, performing linear discriminant analysis dimensionality reduction to obtain two LDA expressions, and obtaining a shaffler-like tissue prediction map according to the decision boundary straight lines of the corresponding three tissue types. Most material organizations can be correctly classified through the method, the accuracy is high, and the method is convenient to popularize and use in new materials and design components.

The invention discloses a metamorphic rock area crystalline graphite ore prospecting method and system, and the method comprises the following steps: S1, constructing a structure-mineral-mineralization dynamic adaptation model: dividing the structure type of a target area, and building the corresponding relation of the structure type-ore body occurrence position; according to the method, the graphite flake diameter and the graphitization degree are analyzed, and a mineral characteristic-mineralization stage-resource potential correlation model is established. According to the prospecting method and system for the crystalline graphite ore in the metamorphic rock area, geoelectric data can be collected in all directions and a three-dimensional ore body prediction model can be generated through the arranged prospecting system in cooperation with constraint of a structure-mineral-mineralization dynamic adaptation model, the extension direction, the scale and the occurrence state of a deep ore body are clearly described, and the prospecting efficiency is improved. The detection limitation of a traditional two-dimensional technology is effectively broken through, the hidden ore body missed judgment risk is greatly reduced, and accurate target area guidance is provided for subsequent drilling.

The application discloses a controllable gradient and non-gradient nitriding layer, a preparation method and application thereof, and belongs to the technical field of metal material surface strengthening. The application realizes controllable transformation of the structure type of the nitriding layer by adjusting and controlling the component characteristics of a base material and ion nitriding process parameters. The application realizes designable adjustment and control of the structure of the nitriding layer by establishing the corresponding relationship between the material component and the nitriding behavior, so that the target structure type can be selected according to different service requirements, and the application has wide application prospects in the field of metal material surface strengthening.

The application discloses a financial problem analysis method and device based on a large language model, equipment and a medium, relates to the technical field of natural language processing, and comprises the following steps: searching a target subgraph corresponding to a financial problem to be analyzed from a knowledge graph, and performing topological analysis on the target subgraph to obtain a structure representation vector; determining a graph structure type by using the structure representation vector, and determining a prompt word template based on the graph structure type; determining the priority of each node corresponding to the financial problem to be analyzed based on the semantic correlation and time correlation between each node in the target subgraph and the financial problem to be analyzed and the PageRank score of each node, reordering each node according to the priority to obtain a target logic flow, and filling the prompt word template by using the target logic flow to obtain a target prompt word; and inputting the target prompt word into a large language model to generate an analysis result. The structure representation vector is obtained through topological analysis, and the problem of disorganized context in the generated result is solved.

The invention relates to a well logging technology, and discloses a multilayer stratum inversion method of a while-drilling electromagnetic edge detector, which comprises two stages of offline training and online inversion. In the offline stage, firstly, multiple stratigraphic structure types are constructed, and training samples are generated; performing feature enhancement and reconstruction on the forward modeling original response vector of the sample to improve the data dimension and sensitivity; then, for each stratum type, training through a supervised descent method to obtain a special gradient optimization set; in the online stage, the same feature reconstruction is carried out on the original response measured in real time, the stratum type to which the original response belongs is intelligently judged, and the matched gradient optimization set is automatically called to carry out rapid iterative inversion. Dynamic attenuation regularization and geological prior constraint are fused in inversion iteration, noise is effectively suppressed, and stability and geological rationality are guaranteed. According to the method, rapid, accurate and stable inversion of a complex multi-layer stratum is realized, and the reliability of geosteering while drilling is remarkably improved.

The application discloses a data backup method and system based on a multi-dimensional structure, which comprises the following steps: obtaining target data to be backed up and corresponding data source information; determining a plurality of structural data parts corresponding to the target data and corresponding structural types based on a data structure analysis algorithm; determining a backup priority corresponding to each structural type according to the data source information; and determining a backup position and a backup order of each structural data part when the target data is backed up to a target server according to the backup priority and the structural data parts. It can be seen that the application can realize accurate backup management based on multi-dimensional data structure and source, improve data backup efficiency and security, and reduce the risk of data loss.

The invention provides a processing technology generation method and device, electronic equipment and a readable storage medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining model data of a processing object; identifying the model data to obtain first geometric data of a plurality of structure types corresponding to the processing object; a machining tool and a machining procedure corresponding to each structure type in the multiple structure types are determined, the multiple structure types comprise the first type, and the machining tool and the machining procedure corresponding to the first type are determined based on the machining feature and the feature size corresponding to the first type; the processing feature and the feature size corresponding to the first type are generated based on first geometric data of the first type; and generating a machining process flow based on the machining tools and the machining procedures corresponding to the multiple structure types, wherein the machining process flow is used for machining to obtain the machined object. The generation efficiency of the processing technological process can be improved.

The present specification provides a method and device for determining the micro-topological structure of the pores of a tight sandstone reservoir, which comprises: determining the pore type, pore size and throat type in a plurality of rock sample slices of the tight reservoir; determining the porosity and permeability; performing high-pressure mercury injection experiments and constant-speed mercury injection experiments and recording the experimental data; determining the pore throat size and distribution characteristics and the main combination configuration relationship between the pore type and the throat type according to the experimental data; processing the experimental data to obtain the fractal dimension under the full pore size; and determining the micro-topological structure characteristic table of the pores of the tight sandstone reservoir according to the above parameters. The scheme can comprehensively understand the pore structure characteristics of the reservoir through the multi-type pore throat topological structure pore throat model, finely characterize the scale, precision and pattern of the pore structure, clearly define the pore structure type, mode and the differences in the reservoir quality and the fluid permeation characteristics under different types of pore structure, and can classify the reservoir.

A system may attempt to classify, according to field types, label fields used by structures in instances of different log data source types, which use different structure types and different path information to access the structures of those structure types within the instances. Each of the structures includes at least one of the label fields and at least one data field associated with that label field. The system may store a result that includes the path information to access the structures and mappings of at least some of the field labels to the field types. The system may determine a field type involved in a system level query, and then generate a set of query graphs based on the field type and the result. The system may generate a set of instance level queries for a set of the instances according to the set of query graphs.

The present application relates to the technical field of numerical simulation analysis, and particularly relates to a typical structure identification method, device, equipment, storage medium and program product. The method comprises the following steps: obtaining a three-dimensional particle point set of a target to be identified, and calculating porosity, directional eigenvalue, overall linearity, overall flatness and sphericity based on the three-dimensional particle point set; determining whether the target to be identified belongs to a first typical category set, a second typical category set or a third typical category set based on the porosity; when the target to be identified belongs to the first typical category set, identifying the typical structure of the target to be identified based on the porosity; when the target to be identified belongs to the second typical category set, identifying the typical structure of the target to be identified based on the sphericity; and when the target to be identified belongs to the third typical category set, identifying the typical structure of the target to be identified based on the directional eigenvalue, the overall linearity and the overall flatness. The method can effectively improve the efficiency of structure type identification and space debris impact spacecraft risk simulation evaluation.

The invention relates to the technical field of computers, in particular to a BIM (Building Information Modeling)-based engineering cost control method, which comprises the following steps of: firstly, extracting three types of core keywords, namely building and structure types, building sizes and building quantities, from a construction scheme, and constructing a BIM model based on the keywords; dividing the model into a plurality of areas, calculating the complexity characterization value of each area, and determining the type and dosage of raw materials according to the building structure size of the area; the method comprises the following steps: obtaining specific value sub-parameters of raw material unit price, building and structure processing cost, combined processing cost, structure size and complexity, carrying out weighted summation, calculating regional estimated cost, comparing the estimated cost with preset cost, analyzing a deviation reason by combining the distribution condition of the estimated cost of each region, and determining the distribution condition of the estimated cost of each region by analyzing the distribution condition of the estimated cost of each region. The method can quickly distinguish whether the deviation originates from the disqualification of the cost calculation mode or the disqualification of the modeling process, replaces a traditional manual one-by-one troubleshooting mode, and greatly improves the troubleshooting efficiency and accuracy of the deviation problem.

The application discloses a kind of grasshopper-based space tensile structure parameterization modeling method, steps are as follows: picking up the building skin three-dimensional model of the tensile structure to be established;Determine the structure type and geometric control parameter, call input operator input parameter;Based on the input parameter, call the packaged tensile beam wireframe model generation operator or tensile truss wireframe model generation operator, obtain the three-dimensional wireframe model of tensile structure.The application can quickly establish the three-dimensional model of tensile structure according to building surface, and the structure type and geometric parameter can be freely controlled, the design method is simple and efficient, which provides great convenience for structure type finding, scheme comparison, calculation analysis and optimization design of space tensile structure.

The invention discloses a retrieval method, device and equipment and a computer storage medium, under the condition that a problem is obtained, through a structure router, semantics and a structure of the problem are analyzed, and a structure type corresponding to the problem is identified; rebuilding scattered text knowledge extracted from the original document into structured knowledge through a knowledge constructor, and generating description information of the structured knowledge; decomposing the problem according to the description information of the structured knowledge through a problem decomposer to obtain a plurality of sub-problems; through a knowledge analyzer, an answer corresponding to each sub-question is extracted from the structured knowledge; and finally, summarizing the answers corresponding to the sub-questions to obtain the answer of the question. According to the embodiment of the invention, the flexibility and accuracy of information retrieval can be improved in the face of knowledge-intensive tasks with dispersed information.

The invention provides a structure-to-instance theorem automatic formalization method and device, and relates to the technical field of natural language process.The method comprises the steps that mathematical structure types of non-formalized problem description texts are recognized, and formalization files from structures to instances are generated for each mathematical structure type; performing type check on the generated code of the formalized file, and when the check is not passed, correcting the generated code according to a preset error correction strategy to obtain a skeleton file lacking theorem proof; calling a large model to generate a certification code of each theorem certification, and synthesizing the certification codes into the skeleton file to obtain a formalized code file; and translating the formalized code file back to obtain a formalized problem description text corresponding to the problem description text. The method is used for solving the problems that in the prior art, automatic formalization work lacks the structural understanding ability for mathematical knowledge, and the automatic formalization deduction process from the structure to the theorem is difficult to achieve.

The invention relates to the technical field of numerical simulation analysis, in particular to a typical structure identification method, device and equipment, a storage medium and a program product. Comprising the following steps: acquiring a three-dimensional particle point set of a to-be-identified target, and calculating porosity, a direction characteristic value, overall linearity, overall flatness and spherical degree based on the three-dimensional particle point set; judging whether the to-be-identified target belongs to a first typical category set, a second typical category set or a third typical category set based on the porosity; when the to-be-identified target belongs to the first typical category set, identifying the typical structure of the to-be-identified target based on the porosity; when the to-be-recognized target belongs to the second typical category set, recognizing the typical structure of the to-be-recognized target based on the sphericity; and when the to-be-identified target belongs to the third typical category set, the typical structure of the to-be-identified target is identified based on the direction characteristic value, the overall linearity and the overall flatness, and the efficiency of structure type identification and space debris impact spacecraft risk simulation evaluation can be effectively improved.

The application provides an additive manufacturing process parameter matching method and system, and relates to the technical field of metal additive manufacturing.The three-dimensional model of a part to be manufactured is introduced and converted into point cloud data, and standardized point cloud data is obtained through decentralization, scale normalization and uniform sampling; the local geometric features and global topological features of the data are extracted, and the entity structure of the three-dimensional model is partitioned; process parameters are matched in a mapping database based on the structure type, and when there are multiple groups of parameters, the optimal parameters are selected through a forming quality evaluation function, and the scanning path strategy is one-to-one corresponding to the structure type; the parameters are converted into control instructions to generate a process configuration file.The application realizes accurate matching of structure-level parameters, reduces manual intervention, improves forming quality and manufacturing stability, completes the automation of the closed loop from design to manufacturing, and is suitable for different additive manufacturing equipment.