906 results about "Database construction" patented technology

The invention relates to the technical field of database construction, in particular to a knowledge base question-answering system construction method and device, equipment and a storage medium. The method comprises the following steps: acquiring a user question instruction, and performing part-of-speech tagging and keyword vectorization on a target text to generate a retrieval text keyword vector; performing semantic linear embedding and spatial projection processing on the keyword vectors to obtain keyword semantic vectors; logic mining is conducted on the keywords, a logic relation set among the keywords is obtained, logic recognition is conducted on the target text based on the relations, and retrieval text logic is generated; performing matching retrieval with semantic vectors in a knowledge base to obtain a candidate semantic query data set; and performing coherent logic retrieval on the candidate data set according to the retrieval text logic and the keyword vector to generate a final retrieval target answer. According to the method and the system, more accurate and efficient knowledge base question-answering system construction is realized.

The invention discloses a polyethylene plastic hollow plate defect detection method and system, and relates to the technical field of nondestructive testing, the system is composed of a plurality of functional modules, and the system comprises: a multi-mode sensing module for collecting multi-source data including a hollow plate surface image, three-dimensional morphology data and an ultrasonic reflection signal; the historical database construction module is used for performing space-time alignment and feature level fusion on the multi-source data to generate a composite defect feature matrix; collecting ultrasonic signal waveforms of known defects, extracting characteristic parameters, and establishing a historical waveform library; calculating a characteristic parameter classification range of each type of defects based on a historical waveform library; judging whether the detection waveform parameter falls into a classification range corresponding to the processing noise or not, and if so, rejecting the signal; otherwise, keeping; and the defect area identification module is used for dividing the surface of the hollow plate into uniform grids based on the surface image of the hollow plate, and counting the density of the residual ultrasonic detection sources in each grid.

The invention provides a carbon database construction method and system based on regional energy carbon emission prediction, and the method comprises the steps: eliminating the space-time reference deviation of an original data set, and generating an energy activity hologram spectrum with a unified space-time label; inputting the energy activity holographic spectrum into a non-linear correlation program, extracting a carbon release intensity characteristic curve of each energy carrier through a self-adaptive weight distribution mechanism pre-stored in the non-linear correlation program, and constructing a spatial-temporal characteristic network in combination with industrial operation cycle parameters and climate response factors in a target area; the spatial-temporal characteristic network establishes a dynamic coupling relationship between an energy flow mode and a carbon emission hot area to form a carbon emission associated topological structure with a self-organizing characteristic; a three-dimensional carbon database is formed, and the three-dimensional representation and deduction capability of space-time evolution of carbon emission is realized. The system comprises an atlas generation module, a structure construction module and a content fusion module. According to the invention, normal form transformation from static carbon accounting to dynamic carbon metabolism simulation is realized.

The invention belongs to the technical field of aviation energy design, and particularly provides an aviation energy power device fault intelligent inquiry system and method based on a knowledge graph. The method comprises the following steps: firstly, showing a complex data structure and a knowledge relationship to a user in a visual and dynamic manner through knowledge extraction, knowledge graph database construction, knowledge graph visualization and other methods, and constructing a knowledge graph basic framework; according to the method, the depth information of the target object can be extracted from the images from different angles, the fault characteristics of the equipment can be intuitively displayed, and the fault state of the equipment can be visually represented by extracting the depth information of the target object from the images from different angles. The evolution of the equipment state can be tracked through the change of the three-dimensional space; a conversion algorithm of the knowledge graph and the Bayesian network is realized through the Bayesian network, and rapid reasoning of fault causes is realized in combination with a Bayesian network reasoning algorithm; and finally, based on an intelligent inquiry system of a large model, a deep learning technology and a large-scale training model are utilized, and previous fault data and professional knowledge of the aviation energy power device are combined to provide intelligent auxiliary diagnosis support.

The invention relates to the technical field of database construction, in particular to a construction method and system for a reproductive medicine database. The method comprises the following steps: acquiring a biological tissue sample of a patient; acquiring reproductive endocrine hormone data, embryo morphological parameter data, immune cell function data and genome variation data from the biological tissue sample of the patient; performing time sequence analysis processing on the hormone fluctuation mode according to the reproductive endocrine hormone data to obtain endocrine dynamic characteristic data; performing image recognition processing based on coherent superposition characteristics of light on the embryo morphological parameter data, and performing embryo development potential evaluation to obtain embryo development potential data; and performing hierarchical clustering processing on the individual heterogeneity of the patient according to the immune cell function data and the genome variation data to obtain immune-genetic typing data of the patient. By means of the quantum dot sensing technology and the multi-channel micro-fluidic chip, standardization of data acquisition is achieved, and the heterogeneity problem of a data source is solved.

The invention relates to the technical field of dredge pump performance analysis, and discloses a numerical simulation and model test-based dredge pump performance analysis method, which comprises the following steps of: planning an analysis process, and determining numerical simulation (dredge pump internal flow field simulation) and model test contents (actually measured performance data under different working conditions); determining working condition types according to design parameters and working conditions; generating a performance analysis process set and determining an execution sequence; generating a simulation parameter setting list and a test scheme list of each working condition; and associating the data to generate an overall scheme. The method further relates to working condition analysis boundary determination, working condition type subdivision, dynamic adjustment of the process, test rule optimization, database construction and the like. According to the method, comprehensive and accurate analysis of the dredge pump performance is achieved through multi-dimensional data integration and a dynamic mechanism, the analysis efficiency and reliability are improved, and the method is suitable for evaluation and optimization of the dredge pump performance.

The invention relates to a smart city planning monitoring system, which comprises a multi-source data acquisition module, a database construction and management module, a planning analysis and monitoring module, a communication cooperation module and an interactive decision support module, the database construction and management module is used for constructing and managing a database of urban planning and monitoring data, the planning analysis and monitoring module is used for planning scheme evaluation and progress tracking, the communication cooperation module is used for data communication and module cooperation, and the interactive decision support module is used for data interaction, monitoring visualization and decision support. According to the smart city planning monitoring system, a city planning multi-source data fusion algorithm based on kernel density analysis is put forward to fuse multi-source data, and a smart city planning monitoring algorithm based on analytic hierarchy process and fuzzy comprehensive evaluation is put forward to monitor and evaluate smart city planning.

The invention provides a traditional Chinese medicine intelligent health diagnosis system and method based on multi-source data fusion, and relates to the technical field of health diagnosis. The system comprises a database construction module which is used for collecting condition data and historical disease data of a patient and constructing a traditional Chinese medicine holographic health database. And the multi-dimensional classification module is used for establishing a multi-source data classification standard and adding category fields to the multi-source data in the traditional Chinese medicine holographic health database from multiple dimensions to obtain associated field data. The importance classification module is used for constructing an importance degree judgment standard and judging the importance degree of different associated field data to obtain importance labels, and the exclusive customization module is used for classifying health states according to different importance labels to obtain current health data and formulating exclusive treatment strategies. According to the method, the data are classified and associated from multiple dimensions, the organization and utilization efficiency of the data is improved, and the importance degree judgment method can provide a basis for priority processing and analysis of the data.

The invention discloses a construction method and system for a membrane material database, and relates to the technical field of database construction.The construction method comprises the following steps that in the operation process of a database management system, multi-dimensional parameter information generated by the system is collected in real time, collected original data is cleaned and preprocessed, different types of data are normalized, and a database management result is obtained; and the consistency and the validity of the data are ensured. According to the method, the multi-dimensional parameters of the database management system are collected in real time, cleaning and anomaly analysis are carried out, the system intelligently evaluates the operation state, the operation anomaly coefficient is generated, and early warning and fault prediction are achieved. Based on the comparison between the abnormal coefficient and the multi-level threshold, the system divides the risk into low, middle and high levels, and takes corresponding measures. According to the refined management mechanism, the stability of the database is effectively improved, data loss, inconsistency and crash are prevented, and the accuracy and efficiency of fault processing are improved.

The invention relates to a knowledge graph question-answering method and system based on a large language model. The method comprises the following steps: constructing a large language model framework and finely adjusting training data; finely adjusting the large language model based on LoRA; sub-graph retrieval and knowledge graph database construction; and large language model reasoning and answer generation. By using an innovative scheme of combining the large language model and the knowledge graph, the accuracy, flexibility and reasoning ability of the system can be remarkably improved by combining the strong semantic understanding ability of the large language model and the structured knowledge of the knowledge graph, the limitation of the intelligent question-answering system in processing complex and changeable problems is solved, and the intelligent question-answering system is more intelligent. Especially in scenes needing cross-domain reasoning and background knowledge support, the method can adapt to wider fields and application scenes.

The invention discloses an MES (Manufacturing Execution System) login authentication method based on a face recognition technology, which relates to the technical field of industrial information security, and comprises the following steps of: constructing an authentication data acquiring a face image of an authorized user of an MES, extracting a reference face feature template after preprocessing, and constructing the authentication database; performing associated storage on the reference feature template, user identity information, preset operation authority and affiliated production station information to form an authentication database; according to the method, spoofing attacks are prevented through multi-mode living body detection, and the problem that a traditional password / key is easy to leak and borrow is solved in combination with uniqueness of human face biological characteristics; a person-post-terminal binding mechanism further limits permission abuse, and internal operation risks are reduced; the non-contact authentication does not need to memorize a password or carry a physical key, and is suitable for a working scene that a workshop operator wears gloves and holds tools; and the recognition passing rate in a complex industrial environment is improved through dynamic threshold optimization.

The invention relates to the technical field of data information extraction, in particular to a bidding document qualification information intelligent extraction method based on a knowledge graph and hybrid retrieval, which comprises the following steps: a document preprocessing and partitioning step: preprocessing and partitioning a bidding document to obtain a plurality of document blocks; a vector database construction step: vectorizing the document blocks, storing the vectorized document blocks into a vector database, and constructing an index; a knowledge graph construction step: extracting triads from the document blocks, writing the extracted triads into a graph database to construct a knowledge graph, and constructing an index; a mixed retrieval step: carrying out mixed retrieval in combination with the knowledge graph and the vector database; a qualification information extraction step: taking the plurality of document blocks returned by mixed retrieval and the corresponding knowledge graph sub-graphs as contexts, and enabling an Agent agent to perform extraction based on the contexts and an extraction template; and finally, structured qualification item information is output. According to the method, high-quality structured extraction of the qualification information in the bidding document can be realized.

The invention belongs to the technical field of medical imaging and digital twinning, and discloses a thoracic cavity whole organ system level lung four-dimensional EIT detection digital motif and a library building method, and the method comprises the following steps: S1) segmenting multiple organs such as double lungs, heart, sternum, rib and thoracic vertebra central axis skeleton, main bronchus and esophagus based on an individual CT image, and building a three-dimensional geometric model integrated with an EIT electrode array; s2) simulating breathing dynamic deformation by using a solid mechanical model; s3) establishing a coupling relationship between deformation and conductivity, and generating dynamic three-dimensional conductivity distribution; s4) solving an electromagnetic field positive problem, and generating a virtual EIT voltage database synchronous with respiration; the invention also covers pathological model integration and data enhancement strategies. According to the method, a high-fidelity, large-scale and diversified EIT virtual data set can be generated, core data support is provided for training and verifying an AI intelligent reconstruction algorithm, and a model foundation is laid for developing a lung function dynamic digital twinning system.

The invention discloses a sewage data management system and method based on kitchen garbage treatment, and relates to the technical field of data management. The system comprises a data acquisition and historical database construction module, a correlation analysis and dynamic response rule construction module, a sewage data trend pre-judgment module and an operation regulation and data updating module. The data acquisition and historical database construction module is used for acquiring garbage treatment load and sewage data and constructing a historical database covering time period fluctuation and seasonal periods; the correlation analysis and dynamic response rule construction module constructs a dynamic response rule and determines the time delay duration; the sewage data trend pre-judging module is used for acquiring load data in real time and pre-judging a future sewage change trend; and the operation regulation and data updating module adjusts parameters of the sewage treatment system, collects effluent data to construct a new sample, supplements a database and updates a dynamic response rule. According to the invention, accurate sewage data management is realized, and the operation efficiency and stability of the sewage treatment system are improved.

The invention belongs to the technical field of three-dimensional modeling systems, and particularly relates to an urban geological complex geologic body three-dimensional modeling system which comprises urban geological database construction, three-dimensional model construction and underground space resource development potential evaluation. The urban geology database construction comprises the steps that the database construction target is to establish an urban geology and underground space database; the system is positioned as a basic data center on which urban geology and underground space depend, a convergence place of various data required by accident emergency processing, an information management and control center of various geology and underground space built in the whole life cycle of a city, a data exchange hub and an auxiliary support data center. In the aspect of database construction, efficient management and comprehensive application of urban geological data are realized through standard architecture, classified storage, safety measures and a reasonable updating mechanism.

The invention relates to the technical field of data processing, and discloses a medical care knowledge graph database construction method and device based on a creative system, and a medium, and the method comprises the steps: calculating the sparseness of each original node in a basic medical care knowledge graph, and screening out sparse nodes according to the sparseness; traversing the basic medical care knowledge graph, acquiring original nodes which are not directly connected with the sparse nodes, marking the original nodes as to-be-mined nodes, and judging whether a potential relationship exists between the sparse nodes and the to-be-mined nodes or not; when it is judged that the potential relation exists, specific representation of the potential relation between the sparse node and the node to be mined is deduced; creating and adding a new relation edge for the basic medical care knowledge graph according to the specific representation of the potential relation so as to form an optimized medical care knowledge graph; the structure of the graph can be enriched, the overall integrity of the medical care knowledge graph is improved, and then the search accuracy is enhanced.

The invention belongs to the technical field of composite material design, and discloses a polyimide-based composite material design method and system based on experiment-machine learning collaborative optimization. The method comprises the following steps: S1, experimental database construction and machine learning performance modeling; S2, machine learning model construction and training; S3, model evaluation and performance index output; and S4, intelligent design of the polyimide-based composite material. The multi-objective performance collaborative optimization design and preparation of the polyimide-based ternary carbon heterostructure composite material are carried out by taking experimental data as a main material and machine learning as an auxiliary material. According to the method, an experiment-model-optimization closed-loop iterative design system is constructed based on an experiment-machine learning collaborative optimization method, the method has the advantages of high prediction precision, high optimization efficiency, good multi-target adaptability and the like, the development efficiency of the polyimide-based composite material is remarkably improved, and the development cost of the polyimide-based composite material is reduced. The method is suitable for intelligent design and large-scale application and popularization of the high-performance heat-conducting electromagnetic shielding material.

The invention relates to the technical field of continuous casting equipment, and discloses a crystallizer control method and system based on proportional integral differential, and the method comprises the steps: converting analog signals of liquid level height and wall surface temperature into analog control signals, and adjusting parameters of a cooling water inlet of a crystallizer; constructing a cooling water database according to the flow and temperature of the generated cooling water and the heat transfer information of each area in the crystallizer; calculating proportional control output which is in direct proportion to the difference value, calculating integral of past errors, predicting changes of the errors, combining the outputs of all the parts, and calculating a final control signal; according to the calculation result of the final control signal, the flow and the temperature of cooling water are adjusted, and the liquid level height and the wall surface temperature in the crystallizer reach set values. The system comprises a database construction module, an intelligent control module and a result evaluation module. According to the invention, the operation performance of the crystallizer is effectively maintained, and support is provided for further improvement.

The invention relates to a knowledge graph-based teaching resource database construction method and system, and belongs to the technical field of data resource processing, and the method comprises the following steps: S1, obtaining and preprocessing a multi-source heterogeneous teaching resource: carrying out the natural language processing of an unstructured text to recognize the association of an entity and a key concept, analyzing the user behavior log to extract hidden knowledge point association; s2, defining a multi-dimensional teaching knowledge graph mode layer: constructing a multi-dimensional graph mode layer; s3, collaborative extraction and fusion of graph entities and relationships: collaborative extraction of core teaching entities and specific relationship types from the preprocessed teaching resources to construct a knowledge graph; s4, adaptive graph updating and teaching path generation: taking the constructed knowledge graph as an underlying database, and responding to knowledge state query of a user; the method has the beneficial effects that massive and heterogeneous teaching resources and the knowledge graph are effectively fused.

The invention provides a broadband oscillation mode identification method and device, equipment and a storage medium, and the method comprises the steps: firstly collecting new energy power grid oscillation data, segmenting the data, carrying out the dimension reduction processing, and simplifying the data through calculating the average value or characteristic value of each segment; then, classifying the data by using a k-Shape clustering algorithm, and constructing a classification data set; and randomly extracting various samples to train a random forest model to form a pattern recognition model. New data is input into the model after dimensionality reduction to obtain an oscillation mode. According to the method, through data dimension reduction, clustering database building and random forest rapid matching, accurate identification of broadband oscillation data is realized, historical, real-time and simulation data are integrated, and the identification efficiency and accuracy are improved.

The invention relates to the technical field of commodity visual identification, in particular to a vending cabinet commodity visual identification system based on a machine learning model, which comprises a feature extraction module used for determining position information of a target identification commodity, shooting a picture of the position of the target identification commodity to obtain a commodity image, and performing feature extraction on the commodity image to obtain a feature extraction result; constructing a target identification commodity feature network; the database construction module is used for collecting the feature information and the mutual relation of each commodity in the vending cabinet, processing the feature information and the mutual relation of each commodity, and storing the processed feature information and the mutual relation to a feature database; the matching identification module is used for establishing an association relationship between the image feature information association network and the standard feature information association network, determining feature information matched with the target commodity feature information from the feature database, and determining an identification result of the target commodity based on the commodity corresponding to the feature information, the method can achieve the accurate and efficient recognition of the commodities in the vending cabinet.

The invention belongs to the field of information data processing, and particularly relates to a method for designing a biochemical experiment based on artificial intelligence and a man-machine interaction system. The method comprises the steps of constructing a database; inputting an instruction by a user, identifying user intention, and outputting a preliminary scheme; prompting the user to feed back the initial scheme, if the user refuses to feed back or does not feed back, recording a user instruction and data, and taking the initial scheme as a final output scheme; and if the user feeds back, optimizing the scheme according to the user feedback, and outputting the scheme again. In the aspect of database construction, basic data is constructed by utilizing the basic change rule of biochemical substances, so that the data integrity and reliability are improved. The invention also designs a special algorithm to improve the accuracy of user intention recognition, and optimizes the generated experimental method based on user feedback and historical data, so as to finally obtain the experimental method with scientific process and strong individuation.

The present invention discloses a rule-based automated data governance system and method, and relates to the technical field of data management. The system of the present invention includes: a historical data analysis and rule base construction module, a real-time demand analysis and demand determination module, a data governance simulation and effect evaluation module, and a data governance rule adjustment and application module; the historical data analysis and rule base construction module collects and analyzes historical business demand information and historical data, and constructs a data governance rule base; the real-time demand analysis and demand determination module obtains real-time business demand information and data to be governed, and determines whether it is new business demand information; the data governance simulation and effect evaluation module performs data governance simulation on new demands based on historical data governance rules, and evaluates the data governance effect; the data governance rule adjustment and application module outputs adjustment suggestions according to the evaluation results, supports personnel to adjust and apply real-time data governance rules, and optimizes the data governance process.

The invention discloses a Chinese character structure and geometric space interactive writing method, which relates to the technical field of interactive writing methods, and comprises the following steps: carrying out geometric classification processing on Chinese characters by adopting a structural analysis method to obtain a Chinese character type set comprising a left-right structure, an up-down structure and a surrounding structure; carrying out geometric rule definition processing on the obtained Chinese character type set to obtain a geometric constraint rule base containing component proportion, gravity center alignment and stroke topological relation; performing structured storage processing on the obtained geometric constraint rule base by adopting a database construction method to obtain a dynamically-called Chinese character writing template database; the writing process of the user is monitored in real time, and a writing feature data set containing stroke coordinates, writing speed and pressure data is obtained; performing matching processing on the obtained writing feature data by adopting a dynamic grid generation method to obtain a self-adaptive reference grid corresponding to the currently written Chinese character; and carrying out deviation detection processing on the obtained self-adaptive reference grid by adopting a computer vision method.

The invention relates to a product carbon footprint basic database construction method. According to the method, government supervision data, enterprise live-action data and industry standard data are integrated, a carbon footprint model of a production stage and a full life cycle is constructed in combination with a life cycle evaluation method, data cleaning is performed on original data, carbon footprint factors are graded and dynamically updated based on an energy efficiency level, and a carbon footprint model is obtained. Accurate calculation of industrial chain carbon footprint factors, effective integration of multi-source heterogeneous data and dynamic iteration of a database are achieved, the problems that an existing database is insufficient in regional representativeness, poor in timeliness and low in technical transparency are solved, and finally a localized carbon footprint basic database which is comprehensive in coverage, traceable and compatible with international standards is established. And reliable data support is provided for carbon accounting and international trade barrier coping.

The invention discloses a CKD special disease database construction method and system, and relates to the technical field of database construction, and the method comprises the steps: obtaining and predicating a multi-source heterogeneous atomic fact; constructing and fusing three sets of ontology models; verifying and deducing facts in a layered manner according to a multi-layer priority rule base; calling a constraint completion engine to generate inference facts for missing or conflicting fields; streaming follow-up visit, test and intervention logs into events and triggering graded alarms; an anti-fact intervention scene is simulated for the high-risk patient, and pilot groups are screened; dynamically evaluating and adjusting the rule priority; and based on a causal chain and an event mode, clustering patients and constructing a generality map, and recording a whole-process operation chain. Semantic management is realized through fusion of ontology, anti-fact intervention simulation is performed on high-risk patients by means of multi-layer rule verification, and database semantic consistency, reasoning depth, decision support and traceability are improved through causal atlas driven clustering.

An indoor fire source positioning method based on an infrared thermogram of the outer surface of a glass curtain wall comprises the following steps: database construction, which mainly comprises construction of a fire data set, temperature distribution of the outer surface of the glass curtain wall, and image extraction and processing; a Resnet deep learning model is constructed and trained; and carrying out fire source positioning by using a Resnet deep learning model. In the early stage of fire disaster development, when fire behavior reconnaissance of a super high-rise building fire disaster is carried out, a reconnaissance unmanned aerial vehicle carrying an infrared thermal imager is controlled to fly out of a glass curtain wall of a fire floor, and the position of the reconnaissance unmanned aerial vehicle is adjusted to obtain a complete glass curtain wall outer surface infrared thermal image of the fire floor; an infrared thermal image of the outer surface of the glass curtain wall acquired by the thermal infrared imager is input into the trained Resnet-50 deep learning model, the model analyzes the infrared thermal image to give a position number of a fire source, the position of the fire source can be accurately recognized in the early stage of fire development, the real-time performance and reliability are high, and the fire early warning capacity and rescue efficiency of the super high-rise building are improved.

The invention relates to the technical field of intelligent recruitment management, and discloses an intelligent matching recruitment management system based on a large model. The system comprises a talent database construction module which collects multi-dimensional ability characteristics of job seekers and enterprise post demand data and generates a three-dimensional recruitment data set containing ability, post and time dimensions; the personnel post adaptation field modeling module performs dynamic integrating degree analysis on the data set, constructs a three-dimensional personnel post adaptation field, and identifies adaptation field critical point distribution and a flowing path; the key feature screening module extracts core adaptive features meeting a threshold value; the large model matching engine module inputs the core adaptive features into a pre-training large model generator, introduces adaptive field topology and feature continuity constraints, and outputs optimized dynamic adaptive field distribution; the environment variable compensation module fuses the dynamic indexes of the labor market to generate compensation parameters, and corrects the core adaptation features; and the strategy generation module generates a post matching strategy set and a talent optimization path to adapt to the requirements of the recruitment market.

The invention discloses a high-speed rail vehicle body aluminum alloy material corrosion fatigue performance simulation method and system, and belongs to the technical field of material corrosion fatigue testing. The method comprises the following steps: acquiring multi-source data of a high-speed rail body aluminum alloy material on an actual service route; establishing a material corrosion conversion coefficient database; obtaining an equivalent mapping relation based on the service environment and the load input set; generating a laboratory equivalent accelerated environment spectrum; and executing the laboratory equivalent accelerated environment spectrum, obtaining material failure data, and if the comparison difference is not less than a preset threshold value, correcting the calculation parameters of the equivalent mapping relation and regenerating the spectrum system. Through synchronous acquisition and fusion analysis of the multi-source environmental data and the mechanical load and in combination with the corrosion conversion coefficient database construction and closed-loop verification optimization method, the problem of test result distortion caused by separation of a laboratory simulation environment and an actual service condition in the prior art is solved.

The invention belongs to the technical field of composite material design, and discloses a polymer composite material design method based on LLM knowledge database construction and reasoning optimization, and the method comprises the following steps: S1, target performance setting; s2, constructing a knowledge database; s3, constructing a reverse design model; s4, constructing a performance verification module; and S5, performing multi-round test-verification design loop optimization. According to the method, an intelligent design method integrating target setting, semantic knowledge database construction, a design assistant, a performance verifier, a prompt engineering module and a language model material knowledge system is provided, closed-loop reasoning and feedback of structure-mechanism-performance are achieved through multiple rounds of DA-VM collaborative optimization, and the design efficiency is improved. The method has the advantages of high design efficiency, strong structure generation rationality, accurate performance prediction, knowledge evolvable and the like, and is suitable for intelligent rapid development of the high thermal conductivity-wave absorbing-shielding-mechanical integrated functional polymer composite material.