232 results about "Structure generation" patented technology

The invention relates to a training method for providing an underwater vehicle main body structure design model and an underwater vehicle main body structure generation method. The training method of the underwater vehicle main body structure design model comprises the following steps: firstly, generating a noise adding main body structure based on a randomly initialized ordinal number stamp k, a sample main body structure and randomly initialized Gaussian noise generation data; secondly, determining predicted Gaussian noise data based on the ordinal number stamp k, the performance parameters of the sample main body structure and the noise adding main body structure by adopting a main body structure design model; and finally, determining a training loss function based on the generated Gaussian noise data and the predicted Gaussian noise data, and training the main structure design model based on the training loss function. Under the condition that only few sample main body structures exist, enough training sample data used for main body structure design model training can be generated, and model training under a small amount of sample main body structure data is achieved.

The application discloses a standard document writing method and system based on knowledge retrieval enhancement, comprising the following steps: acquiring field multi-source heterogeneous knowledge by knowledge retrieval and constructing a field knowledge graph and a content increment model; performing semantic extraction, structure division, content segmentation and text granularity perception; determining first matching information and second matching information; matching standard paragraph structures and standard sentence structures to generate a standard template; performing compliance review to obtain a compliant text and recommended text; performing abnormality screening and abnormality correction to obtain a compliance value; inputting the compliant text, the recommended text and the compliance value into the content increment model to perform normalized conversion to obtain standard materials; and inputting the standard materials of each sentence into the standard template to obtain a standard document. The method can improve the efficiency and accuracy of standard document writing, has good interpretability, and can be directly applied to a standard document writing system based on knowledge retrieval enhancement.

The invention discloses an automatic design and optimization system for a hydraulic speed control loop, which takes a large language model intelligent body as a core, realizes automatic design and optimization of the hydraulic speed control loop through semantic comprehension, knowledge retrieval and parameter optimization, and specifically comprises an LLM intelligent body, a data processing module and a data processing module, the analysis module is used for analyzing natural language input containing design requirements and performance targets of a user, generating a loop structure in combination with a local knowledge base and calling an optimization algorithm; the local knowledge base comprises a basic hydraulic loop, a key empirical relationship and a typical structure template which are artificially extracted; and the simulation and optimization module is used for executing a swarm intelligence optimization algorithm to optimize and adjust parameters of the loop structure. The invention constructs a hydraulic speed control loop automatic design and optimization system with semantic understanding, automatic generation and adaptive optimization capabilities, and aims to realize full-process intelligent design from user demand input to loop structure generation and performance optimization.

The invention discloses a server power supply system, a server, a topological structure generation method and a storage medium, and relates to the technical field of power electronics. According to the invention, a high-voltage centralized conversion-medium and low-voltage distributed distribution two-stage architecture and a physical isolation design of the first direct-current bus and the second direct-current bus are adopted, and an adaptive mounting platform is provided for load nodes such as a super-capacitor node and an energy storage node depending on the second direct-current bus; the mounting number of the load nodes can be determined based on the power required by the load nodes and the voltage and through-flow level of the second direct current bus, and high-voltage power supply conversion and power supply of the load nodes are separated, so that physical isolation of high-voltage direct current of the first direct current bus and low-voltage direct current of the second direct current bus is realized. The high-voltage direct current input is ensured to be safely, efficiently and stably distributed to each load node in the server after being converted. The problems of potential safety hazard and reliability risk caused by direct access of the high-voltage direct current to the load node, poor mounting adaptability of the load node and the like in the prior art are solved.

The invention discloses a data warehouse table structure generation method and device, a medium and a product, and belongs to the technical field of data warehouses. According to the method, the Excel template configured with multiple pieces of source database table structure information is obtained, table field definition is automatically analyzed, the source data type is intelligently mapped and converted into the target data type according to the source database type, meanwhile, partition key fields are automatically recognized based on the preset strategy, and finally a complete and accurate data definition language (DDL) statement is generated. According to the method, remarkable technical breakthrough and value are achieved in practical application, the table building efficiency can be improved by 90% or above, batch processing of hundreds of tables is supported, and manual errors are reduced by 95% or above; mainstream database type conversion is comprehensively supported, and various data models such as Dores are adapted; the method has the capabilities of automatic type detection and conversion, intelligent key field selection and partitioning and bucket dividing strategy optimization.

The invention discloses a tunnel lining structure generation method and device, and relates to the technical field of tunnel engineering.The method comprises the steps that geometric parameters of a four-center circle section are obtained through a data interface; a multi-element polar coordinate system is constructed based on the geometric parameters of the four-center circle section, coordinate calculation is carried out based on the multi-element polar coordinate system, and a structure node coordinate set and a constraint node coordinate set are generated; constructing a finite element model based on the structure node coordinate set and the constraint node coordinate set, and performing internal force analysis on the finite element model to obtain an internal force analysis result; and based on an internal force analysis result, through discretized reinforcement ratio analysis and safety coefficient evaluation, outputting a target reinforcement scheme, and based on the target reinforcement scheme, generating a tunnel lining structure. Model generation is directly driven through parameterized input, the accuracy of load application is improved, and the safety of the tunnel lining structure is guaranteed.

The invention discloses a self-adaptive table structure generation and index optimization method for JSON data driven by a real-time mode, and relates to the field of computer information management application. According to the self-adaptive table structure generation and index optimization method for the JSON data driven by the real-time mode, efficient and automatic persistence from the JSON data to a relational database is achieved through a four-layer technical architecture including dynamic analysis, intelligent mapping, self-healing expansion and index optimization. Comprising a dynamic mode analysis engine which analyzes a JSON nested structure in real time and generates a mode feature tree with weight; the self-adaptive storage engine is used for dynamically generating or expanding a table structure according to the mode feature tree and executing data type mapping; the index optimizer is used for automatically creating / cleaning indexes based on query log analysis; and the uniform interface layer is compatible with multi-database dialects and shields bottom layer differences. Dynamic table structure generation, intelligent type inference and storage optimization, self-healing Schema extension, query-driven index self-optimization and cross-database compatibility are realized.

The invention relates to the technical field of computers, and discloses a topological structure generation method, a communication method, equipment, a chip and a program product. The topological structure parameters comprise a plurality of master port identifiers, a plurality of slave port identifiers, a mapping relationship between a plurality of master ports and a plurality of slave ports and first data bit widths of the plurality of master ports and the plurality of slave ports, and the mapping relationship comprises that at least two master ports in the plurality of master ports correspond to the same slave port in the plurality of slave ports, and / or at least two slave ports in the plurality of slave ports correspond to the same slave port in the plurality of slave ports. At least two slave ports in the plurality of slave ports correspond to the same master port in the plurality of master ports; determining communication parameters based on the topological structure parameters, wherein the communication parameters comprise the number of arbiters and arbitration parameters; and generating a topological structure file based on the communication parameters, the plurality of master ports and the plurality of slave ports, the topological structure file comprising connection lines among the plurality of master ports, the plurality of slave ports and the at least one arbiter. A user does not need to manually configure an arbiter and calculate, and the labor cost is saved.

The invention provides a knowledge graph and deep learning fused research course automatic generation method and system. The method comprises the steps of receiving event stream data from a plurality of knowledge sources; performing source identification and theme clustering processing on the event stream, and generating a standardized update demand unit; writing the update demand unit into a temporary change buffer area outside the atlas; inputting the knowledge fragments in the change buffer area into a cross-source semantic alignment model, and executing entity mapping and relation prediction operation; generating a multi-scale updating plan based on the influence hierarchy of the candidate nodes and the edge set, and executing a graph updating operation; based on the updated knowledge graph, determining a learning target and ability dimension of the research course, a required core knowledge point sequence and an association relationship; inputting the core knowledge point sequence into a course structure generation model, and outputting a preliminary study course outline; and generating a final study course by using the course outline. According to the method, the research course can be automatically generated, and the timeliness and accuracy of the course are ensured.

The invention provides a clothing pattern intelligent generation method and system based on multi-modal visual identification, and relates to the technical field of visual identification. The method comprises the following steps: firstly, acquiring clothing image data and text description data, performing unified preprocessing, obtaining a style category label, an appearance attribute label and a local contour key point set through multi-modal visual identification, generating structure semantic elements and geometric anchor points by utilizing a semantic-to-structure mapping knowledge base, and constructing a plate type structure diagram; further analyzing the structural constraint and executing constraint solution to generate a candidate pattern; and in combination with manufacturability verification and constraint correction, closed-loop optimization is formed, a target plate type file meeting the structure and manufacturing requirements is output, and effective connection from semantic recognition to plate type structure generation is realized.

The invention discloses a spatio-temporal trajectory prediction method and device based on a multi-modal condition potential diffusion generation model, electronic equipment and a storage medium, and the method comprises the steps: cleaning and aligning multi-source data such as trajectory data, environment semantics and a road network, and constructing standardized input; extracting spatio-temporal context representation through multi-modal attention, mining an environment topological structure in combination with an iterative graph network, and generating structured node embedding; adopting dual-channel cross-modal attention fusion trajectory dynamic features and graph structure information to form unified semantic representation; the conditional variation auto-encoder fuses feature codes to a low-dimensional potential space, conditional reverse denoising generation is executed by using a potential diffusion model, and a future trajectory sequence is recovered step by step; and light weight of the model is realized through diffusion consistency distillation, and reverse sampling is compressed. Through the multimode topology-diffusion distillation integrated architecture, the precision, continuity and reasoning efficiency of trajectory prediction under sparse noise data are improved, and the method is suitable for scenes such as ecological monitoring, intelligent traffic and navigation.

The invention belongs to the technical field of crossing of rock soil, geological engineering and computer modeling, and discloses a three-dimensional fractured rock anisotropic fragmentation and expansion structure generation method and system, and the method comprises the following steps: generating tightly embedded initial blocks in an expansion domain according to the number of control blocks and the initial equivalent size of the blocks; on the basis of the node information of the initial block, anisotropic fragmentation and expansion mapping geometric transformation is carried out on the cell elements, and node coordinate information after fragmentation and expansion and form control is carried out is obtained; calculating the volume ratio of blocks in the target area to obtain a current volume fraction; extracting a target domain in the extended domain, performing constraint smoothing, abandoning an external block, and retaining node coordinate information in the target domain; and exporting the reserved node coordinate information, the current volume fraction and the geometric structure to obtain the fragmentation and expansion structure.

Embodiments of the present application provide a kind of data screening topology structure generation method and device, wherein the method comprises: determining the target topology structure type corresponding to initial data transmission network from multiple topology structure types, wherein initial data transmission network is used to transmit data according to the corresponding relationship between input port and output port;Determine the target data screening strategy corresponding to target topology structure type, wherein the target data screening strategy is used to indicate the way of multi-stage screening to the data transmitted in data transmission network;According to the target data screening strategy, the target data screening topology structure corresponding to initial data transmission network is generated, and the target data transmission network is obtained. By the present application, the problem of low data screening efficiency in the related art is solved, and the effect of improving data screening efficiency is achieved.

The invention discloses a network topology generation method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: collecting network equipment operation data from a plurality of heterogeneous data sources, and generating equipment relation feature data based on the network equipment operation data; inputting the equipment relation characteristic data into a topological reasoning neural network model so as to predict a connection relation between network equipment and a network hierarchical structure by using the topological reasoning neural network model, and generating topological structure data; determining a corresponding target layout algorithm according to network topology characteristics represented by the topological structure data, and generating a network topological graph based on the topological structure data by using the target layout algorithm; and pushing the network topological graph to a visual interface for rendering display. According to the invention, the accuracy of network topology generation is improved.

The application relates to the technical field of computer-aided design of high polymer materials, and discloses a polyimide molecular structure generation method and device based on monomer combination, which comprises the following steps: constructing a synthesizable monomer database; constructing a molecular performance prediction model; generating a target polyimide structure based on Monte Carlo tree search; and outputting a candidate scheme. The device corresponds to the method. According to the application, the chemical search space is controlled within a reasonable and operable range by limiting the basic construction monomer; the actual synthesizability of the generated structure is guaranteed from the source by combining the commercially available or known synthesizable monomers; and the intelligent algorithm is used to systematically explore the monomer combination space, so that the discovery efficiency of novel high-performance polyimide materials is significantly improved.

This application proposes a model-based question-answering method and apparatus for generating context based on grammatical structure. The method includes: selecting multiple initial code fragments related to the question information from a target code library; obtaining a source code file containing any one of the initial code fragments; locating a first code block node corresponding to the initial code fragment from the abstract syntax tree of the source code file; locating all ancestor nodes of the first code block node from the abstract syntax tree and extracting the code structure information of each ancestor node; generating a target code fragment based on the code structure information of the first code block node and all ancestor nodes; concatenating multiple target code fragments to obtain a target context; and inputting the target context into a question-answering model so that the model outputs answer information based on the target context. The embodiments of this application can effectively improve the question-answering performance of the model.

The invention discloses an automatic valve structure design method and system based on generative AI, and belongs to the technical field of industrial equipment intelligent design and artificial intelligence crossing. The method comprises the following steps: 1, valve structure multi-dimensional representation and data set construction; 2, training a conditional generative AI model; thirdly, a valve structure is automatically generated; fourthly, quickly verifying and optimizing a generated result; and 5, reconstructing and outputting the three-dimensional parameterized model of the valve. The method is realized through a valve structure automatic design system, and comprises five modules of valve data set construction, conditional generative AI model training, valve structure generation, verification and optimization, and valve three-dimensional parameterized model reconstruction and output. A novel high-performance valve structure with a non-traditional topology and a flow channel can be generated, a plurality of Pareto optimal schemes can be provided at a time, and the whole-process, automatic and intelligent structural design of the valve from performance requirements to model production and manufacturing is achieved.

This material designing device is provided with: a search unit (121) that sets a generation condition (21) for generating a three-dimensional structure (23) of a material, the generation condition (21) including information indicating at least one of the characteristic and structure of the material; a cross-sectional image generation unit (123) that generates a cross-sectional image (22) of the material on the basis of the generation condition (21) set by the search unit (121); and a three-dimensional structure generation unit (124) that generates the three-dimensional structure (23) of the material on the basis of the cross-sectional image (22) generated by the cross-sectional image generation unit (123).

The application discloses a kind of integrated circuit clock tree optimization method and system based on graph neural network and reinforcement learning, comprising the following steps: step S1: construct graph structure generation module, according to integrated circuit layout to construct the graph structure with register as node, with timing path as edge;Step S2: construct GNN feature extraction module, for the high-dimensional graph embedding representation of the feature vector of register node according to the graph structure constructed;Step S3: construct reinforcement learning network decision module, for receiving current node embedding representation vector and generating specific action after data processing;Step S4: construct timing verification and reward calculation module, for evaluating the updated circuit state, and obtaining reward signal to be used for the training of reinforcement learning network decision module;Step S5: constantly train reinforcement learning network decision module, until training is completed, finally obtain optimized register node feature vector, that is, optimized clock tree.

The application discloses a kind of thermotechnical hydraulic model topological structure generation method, equipment and medium, belong to thermotechnical hydraulic simulation software field, including steps: S1, identification model connector;S2, read model parameter, read and save the model parameters of upstream and downstream nodes on connection line, the upstream and downstream nodes on connection line include pipe and connector;S3, generate graph data structure, generate graph data structure vertex and edge and error for connection error;S4, generate topological structure, traverse vertex and number pipe and connector, and connect upstream and downstream;S5, supplement topological structure information, and give the initial parameters of pipe and connector to the corresponding node in topological structure.This application not only can identify visual pipe modeling connection relationship and quickly and automatically establish topological information structure, but also facilitate program maintenance and subsequent algorithm developer application.

The application discloses a kind of enhanced structure generation method, device, equipment, medium and product.The enhanced structure generation method comprises: obtaining the geometric information of target surface and expected pressure difference distribution;Wherein, target surface is the support surface of target flexible support component, is discretized into multiple grid observation points, each grid observation point corresponds to an expected pressure difference value in expected pressure difference distribution and local geometric feature in geometric information;The expected pressure difference value and local geometric feature of each grid observation point are input into the preset generation network trained in advance, and the local candidate subgraph generated by the preset generation network for each grid observation point is obtained;Local candidate subgraph is fused and processed, and the enhanced network graph structure inside target flexible support component is obtained.The technical scheme of the embodiment of the application can efficiently customize the enhanced network graph structure inside flexible support component according to the expected pressure difference distribution.

The application relates to the technical field of computers and discloses a three-dimensional structure and pose generation method, device, equipment, medium and product. The method comprises the following steps: acquiring a first image and image features of the first image, and acquiring a first three-dimensional structure representation and a first transformation token; the image features, the first three-dimensional structure representation and the first transformation token are injected into a feature interaction module of a third model to obtain a first three-dimensional feature, a first two-dimensional feature and a first transformation parameter; and the first three-dimensional feature and the first two-dimensional feature are aligned by using the first transformation parameter to generate a three-dimensional structure and a camera pose. Thus, joint optimization for three-dimensional structure generation and camera pose estimation is realized, which is beneficial to improving the estimation accuracy of the camera pose and the reconstruction quality of the three-dimensional structure, so that the three-dimensional structure can be aligned with the first image at a pixel level when the three-dimensional structure is projected back to the first image of the original visual angle, thereby ensuring the visual representation consistency of the three-dimensional structure and the first image for a first object.

This invention discloses a method for synthesizing severe weather lidar point clouds by combining real priors with geometrically guided intensity generation. First, a weather simulation module is used to convert clear weather data into pseudo-severe weather data with physical constraints from the statistical regularities of real datasets, constructing a high-quality training set. Then, using a structure-intensity decomposition diffusion model, a high-fidelity geometric structure is generated first through an asymmetric conditional diffusion process, and then matching reflection intensity information is generated based on the structure. This method effectively overcomes the modeling difficulties caused by geometry-intensity coupling in existing technologies, and achieves high-fidelity severe weather point cloud synthesis in the absence of large-scale real data.

The invention discloses an intelligent water affair management system based on deep learning, and the system comprises a data collection and preprocessing module which is used for collecting the data of a water supply network and constructing a standardized water affair input tensor; the topology modeling module is used for generating a water supply pipe network diagram structure and diagram structure representation thereof; the state initialization module is used for fusing the input tensor and the graph structure to generate an initial state vector; the state evolution calculation module is used for establishing an augmented state evolution equation and carrying out adaptive integration to generate a prediction state sequence and source sink estimation; the multi-objective decision module is used for constructing a comprehensive cost function and generating a pump station and valve control instruction; the physical constraint projection module is used for executing water pressure, flow velocity and water age constraint projection and outputting an executable scheduling instruction; and the dynamic simulation feedback module is used for performing digital twin simulation and updating the model and sparse estimation weight. According to the invention, fine control and dynamic feedback optimization of the water affair system are realized, and the operation efficiency and the scheduling intelligence level are improved.

The invention relates to a triple information extraction method and device, computer equipment and a storage medium. The method comprises the steps of obtaining a to-be-extracted document, performing hierarchical analysis on the to-be-extracted document based on a deep learning model to obtain a tree-shaped hierarchical structure of the to-be-extracted document, identifying an association relationship among multiple hierarchies in the tree-shaped hierarchical structure, and generating corresponding triple information according to the association relationship and the tree-shaped hierarchical structure. Due to the fact that the tree-shaped hierarchical structure extracted through the deep learning model can keep the integrity of original information and can accurately recognize the incidence relation between different hierarchies, triple information rich in information can be generated based on the incidence relation, details of an original document can be well reserved, the quality and efficiency of knowledge extraction are improved, and the knowledge extraction efficiency is improved. Richer information is provided for large model writing and question replying, and the model output effect is improved.

The invention is suitable for the technical field of luggage design, and particularly relates to a luggage pull rod dynamic impact strength simulation design method, which comprises the following steps: ensuring the reliability of a design result by obtaining a structure attribute set, a historical attribute set and a design attribute set of a target design luggage; modeling simulation processing is carried out based on the structure attribute set and the historical attribute set, accurate recognition of the high strain energy density area and the geometric weak position of the pull rod is achieved, a feature response set containing the geometric information and mechanical response data of the weak area is obtained, and a clear target spot is pointed out for optimization design; according to the characteristic response set and the design attribute set, variable density lattice structure generation processing is carried out on the high strain energy density area, a traditional empirical design and repeated physical test mode is replaced, the research and development period is greatly shortened, the trial and error cost is reduced, the dynamic impact strength and structural stability of the luggage pull rod are improved, and the service life of the luggage pull rod is prolonged. And reliable technical support is provided for high-performance, light-weight and low-cost design of the luggage pull rod.

The invention relates to the technical field of material generation, and discloses a carbon structure generation method, device and equipment and a medium, and the method comprises the steps: obtaining an initial grid topological structure, a convolutional neural network and a Monte Carlo tree search model; nodes are randomly determined in the initial grid topological structure, carbon atoms are filled in the initial grid topological structure, a first process grid topological structure is obtained, the first process grid topological structure is jointly processed through a first convolutional neural network and a Monte Carlo tree search model, carbon atom filling is conducted, and a second process grid topological structure is obtained; judging whether a carbon structure formed by each node filled with the carbon atoms in the second process grid topological structure conforms to a preset carbon structure rule or not; according to the method, the carbon atoms are jointly filled through the convolutional neural network and the Monte Carlo tree search model, and whether the carbon structure corresponding to the filled carbon atoms conforms to the preset carbon structure rule or not is judged, so that a new carbon structure is quickly and efficiently generated.

The invention relates to the technical field of computer-aided design of high polymer materials, and discloses a monomer combination-based polyimide molecular structure generation method and device, and the method comprises the following steps: constructing a synthesizable monomer database; constructing a molecular performance prediction model; generating a target polyimide structure based on Monte Carlo tree search; and outputting the candidate scheme. The device corresponds to the method. According to the application, the chemical search space is controlled within a reasonable and operable range by limiting the basic construction monomers; combination is carried out based on commercially available or known synthesizable monomers, and the practical synthesizability of the generated structure is guaranteed from the source; the monomer combination space is systematically explored by using an intelligent algorithm, and the discovery efficiency of the novel high-performance polyimide material is remarkably improved.

The invention relates to the technical field of computer aided design, and discloses a precise mold structure parameterization rapid design system based on multi-source data fusion. The system comprises a data acquisition module, a time sequence alignment module, a parameter calculation module, a structure generation module and a verification feedback module, time sequence alignment and fusion are carried out on multi-source heterogeneous data, a multi-target genetic algorithm is adopted to optimize mold key parameters in parallel, and parameter closed-loop correction is realized based on virtual combined simulation. According to the method, the consistency, precision and reliability of mold structure design can be effectively improved.

This invention belongs to the field of power engineering design technology, specifically relating to a method and system for generating and optimizing transmission line schemes based on multi-agent collaboration. The method includes: constructing a collaborative system composed of a specification understanding agent, a spatial exploration agent, and a structure generation agent. The specification understanding agent parses specifications and geographic data, outputs semantically tagged enhanced geospatial data, and generates a dynamic compliance energy field. The spatial exploration agent, guided in real-time by this energy field, explores paths, and its fitness function integrates performance indicators and compliance energy path integrals. The structure generation agent generates tower structure schemes based on paths, loads, and specification constraints. After simulation verification, performance data is fed back to the agents to drive closed-loop optimization. This invention achieves deep real-time collaboration between compliance judgment and optimization search, improving design efficiency and scheme quality.