232 results about "Needs analysis" patented technology

The invention discloses a data knowledge-based method based on semantic fusion, and relates to the technical field of computer information processing.The method comprises the steps that a requirement set serves as input, knowledge requirement analysis, concept modeling, relation modeling and constraint declaration are completed, and a semantic model OB is constructed; taking the original data set Sraw as input, completing standardization processing and structure segmentation under the support of a semantic model OB, and forming an entity corpus and a semantic unit set; based on the semantic unit set, structured and unstructured triple extraction, semantic verification and graph loading are executed, and an initial knowledge graph is constructed; performing entity alignment, relationship merging, rule reasoning and versioning release on the initial knowledge graph to generate a graph; introducing a quality evaluation mechanism, and outputting an optimized atlas and an evaluation document; the KG opt deployment is online, and query packaging, visualization, service arrangement and incremental maintenance are completed. The method aims at solving the problems that multi-source heterogeneous data are not uniform in structure and inconsistent in semantics.

The invention provides a transformer substation AI aided design method based on LLM and RAG, and the method comprises the steps: carrying out the demand analysis through a large language model LLM, and extracting key information; performing knowledge retrieval by using an RAG technology, wherein the knowledge retrieval comprises transformer substation aided design knowledge base construction, transformer substation aided design knowledge retrieval and knowledge reordering; according to the demand analysis and the knowledge retrieval result, the LLM is utilized to generate a preliminary design scheme of the transformer substation, and the design scheme comprises an electrical main wiring diagram, equipment type selection and layout. By adopting the combination of the LLM, RAG and AI aided design, the comprehensive improvement of the design efficiency, standardization and innovation of the transformer substation can be realized, and the problems of low efficiency, insufficient standardization and lack of innovation in the prior art are solved.

The invention relates to the technical field of structured retrieval, and discloses a retrieval enhancement generation method and system based on LLM structured index and vector hybrid retrieval, and the retrieval enhancement generation method based on LLM structured index and vector hybrid retrieval comprises the steps of processing and analyzing a non-structural document, generating a hierarchical tree data extraction with document logic, and generating a hierarchical tree data extraction with document logic. The method comprises the following steps: obtaining a query demand, analyzing and identifying the query demand, self-matching any one or a combined retrieval strategy to quickly and accurately obtain a retrieval result in the complete logic positioning information, optimizing hierarchical tree data by adopting context perception, and establishing the complete logic positioning information in the hierarchical tree data through a reasoning path generation method. According to the method, through structured indexing, accurate positioning of specific chapters of the document, improvement of retrieval accuracy and support of multi-step logical reasoning, the long tail problem which cannot be processed by traditional RAG is solved, a clear and transparent retrieval path can be provided, and the system credibility is enhanced.

The invention relates to the technical field of artificial intelligence, and discloses a contract generation system and method based on multiple agents, and the system comprises a user interaction module which is used for receiving a contract demand inputted by a user and displaying a generation result; the knowledge base module is used for storing and retrieving legal terms, industry specifications and contract templates in a distributed manner; the agent cluster module comprises a demand analysis agent, a law expert agent, an industry expert agent, a risk assessment agent, a language optimization agent and a coordination control agent, the agents interact through a standardized communication protocol, and a coordination strategy is dynamically adjusted based on contract complexity calculated in real time; and full-process automation of contract generation is realized. Through cooperative work of multiple agents, the efficiency and quality of contract generation are improved, the law compliance and industry suitability of the contract are ensured, the risk in the contract generation process is reduced, and the user experience is improved.

The invention discloses an interdisciplinary PBL teaching plan intelligent generation system based on knowledge graph and multi-Agent cooperation, and the system comprises an interdisciplinary knowledge base construction module which constructs knowledge graphs of mathematics, physics and computer subjects through semantic vectorization and entity alignment; the retrieval enhancement module is used for dynamically supplementing knowledge blind areas based on an RAG mechanism; the teaching demand analysis module is used for analyzing teacher input and generating a teaching target matrix; the structured modeling module is used for decomposing tasks and designing a teaching framework according to a three-dimensional target system (cognition, ability and subject literacy); the teaching plan generation module is used for generating subject contents through multi-Agent collaboration; and the teaching plan optimization module verifies interdisciplinary consistency and outputs a standardized teaching plan. According to the method, the knowledge graph and multi-Agent dynamic weight distribution are creatively fused, deep integration of interdisciplinary knowledge is realized, teaching plan generation efficiency and scientificity are remarkably improved, and intelligent lesson preparation support is provided for teachers.

The invention discloses a person and post matching method and system based on talent evaluation. The method comprises the following steps: step 1, setting a talent evaluation standard; 2, establishing an occupational quality model of the personnel; 3, creating a post model; 4, developing a post matching algorithm; 5, internal employee behavior analysis; step 6, a post recommendation system; step 7, quantitative evaluation and demand analysis; 8, a data processing technology; compared with the prior art, the method has the advantages that the scientificity, objectivity, efficiency and accuracy of personnel and post matching are improved, personalized recommendation of employees is realized, the efficiency of talent recognition is improved, and the method has remarkable superiority.

The invention provides a whole-process intelligent management system for stem cell culture medium development, and belongs to the technical field of intelligent management. According to the method, artificial intelligence, big data analysis and knowledge graph technologies are fused, and the whole process from demand analysis, formula intelligent design and virtual simulation, small-scale culture verification and iterative optimization, pilot scale-up process optimization to quality compliance and tracing is covered. All the modules are coordinated through the central intelligent decision engine, the research and development efficiency of the culture medium can be remarkably improved, the development cost can be greatly reduced, and batch consistency and quality stability of the culture medium are ensured by reducing trial and error and optimizing in real time. Meanwhile, a full-chain electronic tracing function is provided, the requirements of laws and regulations for compliance are comprehensively met, and the problems that traditional research and development are low in efficiency, high in cost, unstable in batch and the like are effectively solved.

The invention relates to the technical field of flow forwarding, in particular to a controllable flow forwarding method. The method comprises the following steps: S1, demand analysis, S2, traffic model construction, S3, equipment initial configuration, S4, traffic monitoring and evaluation, S5, traffic classification and priority setting, S6, bandwidth limitation and rate control, S7, load balancing, S8, resource reservation, S9, security encryption and verification of a data packet, S10, traffic caching and data loss prevention, and S11, dynamic adjustment of a forwarding strategy. According to the method, accurate control and management of network traffic are realized through traffic model construction, traffic monitoring and evaluation, traffic classification and priority setting, bandwidth limitation and rate control, load balancing and resource reservation, the security of data in a forwarding process is improved through security encryption and verification of a data packet, log recording and performance monitoring, and the data forwarding efficiency is improved. And data loss is avoided through flow caching, data loss prevention and dynamic adjustment of a forwarding strategy.

The invention relates to the field of user interface design, in particular to a table generation and optimization method and device based on demand analysis, and the method comprises the steps: receiving demand data inputted by a user, and recognizing the attributes of a table, data entities and the relation between the data entities according to the demand data; generating a table structure according to the data entity and the attribute; according to the data entities and the relation between the data entities, target demand parameters are matched, and the target demand parameters comprise data fields and constraint conditions; based on a matching result, filling a table structure with the target demand parameter to obtain an initial table; obtaining an interaction behavior of the user on the initial table in real time, and analyzing demand change data of the user according to the interaction behavior; and updating the initial table based on the demand change data. By analyzing the interaction behavior and demand change of the user, the system can continuously optimize and adjust the table in the use process, so that the table can be automatically adjusted along with the demand change.

The invention discloses an MBSE-based metrological demand analysis method and computer equipment, and the method comprises the steps: constructing a demand model of a complete machine level, taking a complete machine development total requirement demand list as the input, and obtaining an entries complete machine detection and calibration demand as the input of a demand model of a subsystem level; constructing a demand model of a subsystem level, obtaining entries of detection and calibration demands of the subsystem level, and taking the detection and calibration demands as demand model input of an equipment level; constructing a demand model of the equipment hierarchy, and obtaining detection and calibration demands of the entries of the equipment hierarchy; and performing integrated verification and logic verification on the demands of the whole machine, the subsystem and the equipment, completing metrological demand analysis if the verification is passed, and re-constructing the demand model of the whole machine level if the verification is not passed. According to the invention, the metering scheme of the equipment or the engineering product can be automatically realized, the detection and calibration demand information of the equipment or the engineering product is obtained, and the full life cycle of the equipment or the engineering product is prolonged.

The invention discloses an intelligent furniture design system based on AI big data, and relates to the technical field of artificial intelligence, and the system comprises a data collection module which is used for collecting user behavior data, environment data and market data; the data processing module is used for carrying out cleaning, feature extraction and fusion on the collected data to generate structured design input parameters, and the structured design input parameters comprise user preference vectors and spatial constraint parameters; according to the intelligent furniture design system, accurate analysis of design requirements is achieved by comprehensively collecting user behaviors, environment and market data, the problem that design requirement analysis is incomplete due to the fact that a traditional data collection means is single is solved, the system adopts an advanced data processing technology, and the design requirement analysis accuracy is improved. Valuable design input parameters are effectively extracted and fused, a solid foundation is provided for personalized design, and a design generation and optimization module based on a deep learning model can automatically generate and optimize a furniture design scheme.

The present disclosure discloses a system (106) and a method (400) for energy management in a network (108). The method may include initialization by defining input and output parameters (baseline energy cost, optimized energy cost). The method may include performing real-time data collection, systematically gathering real-time metrics and calculating the baseline energy cost. The method may include conducting AI / ML-based prediction for traffic and load forecasting and coverage demand analysis, using historical and real-time data to predict future patterns, and allowing for resource optimization and proactive adjustments. The method may include dynamically adjusting network parameters and calculating and optimizing real-time energy cost (EC), continuously monitoring the network's current EC based on dynamically adjusted parameters. Compare optimized EC with baseline EC, adjusting parameters as needed.

The invention relates to the technical field of computers, and discloses an application development method based on a large model technology, and the method comprises the steps: 1, carrying out the demand analysis, and converting a fuzzy business description into an executable technical scheme through natural language understanding and a structured modeling technology; 2, carrying out architecture design and planning, and constructing a code-free and low-code dual-mode collaborative architecture; 3, establishing a visual arrangement engine, and establishing a dual-mode development interface of a code-free development mode and a low-code development mode; step 4, aiming at different requirements of a code-free scene and a low-code scene, a dynamic adaptation strategy is adopted, and differentiated resource management of lightweight adaptation and elastic expansion is carried out; and step 5, performing field adaptation, and obtaining the industry exclusive capability according to the general model and the field knowledge through code-free rapid adaptation and low-code deep customization. By means of the scheme, the development threshold can be lowered, the efficiency can be improved, and the accuracy of cross-industry application is improved.

The invention discloses a data analysis-driven special equipment safety risk assessment method and system, and relates to the technical field of data processing, and the method comprises the steps: carrying out the safety operation demand analysis of target special equipment, determining the safety operation factor, analyzing a detection point according to the safety operation factor, and laying a sensor group to form a sensing module; target equipment fault data is collected, and a safety risk data set is generated through evaluation and fused into an evaluation tree; and monitoring multi-point operation data of the equipment by using the sensing module, and performing feature analysis and risk assessment in combination with the assessment tree to obtain a safety risk assessment coefficient of the special equipment. The technical problems that in the prior art, potential faults of the special equipment are difficult to monitor and identify in real time through a traditional method, and the real-time performance and accuracy of risk assessment are poor are solved, the potential faults are accurately identified by monitoring the running state of the special equipment in real time, and the risk assessment efficiency is improved. And the real-time performance and the accuracy of safety risk assessment of the special equipment are improved.

The invention provides an intelligent recommendation method and system for industrial design products and a storage medium, and relates to the technical field of product recommendations, and the method comprises the steps: obtaining voice data of a user, and carrying out the comprehensive analysis to obtain a keyword selection coefficient; selecting keywords in a mode of carrying out threshold comparison on keyword selection coefficients, and searching in an industrial design product library by taking the selected keywords as indexes to obtain a first recommended product set; and analyzing a matching condition between the expected price and the material of the user and the price and the material of the product to obtain a second recommended product set, analyzing user interaction data to obtain an interaction score, and recommending the industrial design product with the maximum interaction score in the second recommended product set to the user. According to the method, through deep demand analysis and research on the matching condition of the demand and the recommendation result, the correlation of the recommendation result and the user satisfaction degree are improved.

The invention provides a centralized quantum key relay network and a key distribution method, relates to the technical field of quantum communication, and comprises four steps of relay request initiation and demand analysis, path constraint and decision, cooperative key generation and verification, and monitoring and processing in a transmission process. Through the quantum digital signature, the quantum security MAC check code and the post quantum cryptography signature mechanism, the security of the system facing the quantum computing threat is greatly improved, and meanwhile, the dynamic path selection combining the aging level, the multi-factor dynamic scoring model and the elastic target time window is adopted; according to the method, the optimal path and the target time can be dynamically adjusted according to the timeliness requirement, the path condition and the network state of the request, the path selection is more flexible, different timeliness requirements are met, the integrity and legality of the secret key are ensured by adopting a three-level verification mode, and meanwhile, when the network has a fault, the safety of the network is ensured. A standby path can be automatically switched and a problem node can be isolated.

The invention discloses a multi-agent system based on a large language model, the multi-agent system is used for solving travel planning tasks, the multi-agent system comprises a plurality of agents, each agent is responsible for different travel planning subtasks, and the agents work cooperatively through a structured communication protocol. And sharing information with each other to generate a final travel plan. The intelligent agents comprise a demand analyst intelligent agent, an itinerary designer intelligent agent, a budget planer intelligent agent, a risk assessor intelligent agent and an optimization coordinator intelligent agent, and the intelligent agents complete corresponding tasks according to role division and exchange information through a structured report.

The invention discloses a method and a related device for supervising fuel data of a grassroots thermal power plant by regional branch companies, and belongs to the technical field of regional branch company-level fuel supervising. The method comprises the following steps: defining a plurality of supervising modules and setting supervising rules based on demand analysis of a grassroots thermal power plant fuel management process; abnormal operation or data tampering behaviors in the fuel management process of the basic-level thermal power plant are recognized; checking the supervision basic data corresponding to the behavior data, and completing the collection of incremental data when the data is updated; the supervision data is intelligently analyzed, a visual report is generated, and potential risk fraud behaviors are judged and prompted; and combining a video monitoring module to confirm risk data of the risk point, and inputting the risk data into the intelligent learning training library to complete fuel supervision and control of the basic-level thermal power plant. Through linkage of data safety and intelligent analysis, supervision and intelligent analysis of the whole process of fuel of the basic-level thermal power plant are realized, and the fuel supervision efficiency of the basic-level thermal power plant is optimized.

The invention discloses an electric power knowledge retrieval system based on a large language model, and relates to the technical field of data processing, and the system comprises a training data collection module which is used for collecting professional data and cross-domain general data in the electric power field; the model training module is used for performing internal and external balance training on the hierarchical memory network architecture based on the training data and constructing a large electric power knowledge retrieval model; the retrieval instruction identification module is used for receiving a retrieval demand of a user side and analyzing and generating a disassembly user demand; and the electric power knowledge retrieval module is used for receiving disassembly user requirements and inputting the electric power knowledge retrieval large model to perform electric power knowledge retrieval. The technical problems that an existing power knowledge retrieval system is low in efficiency and poor in accuracy when processing complex documents and cross-domain knowledge are solved, and the technical effect that the power knowledge retrieval efficiency and accuracy are improved through a hierarchical memory network architecture based on a large language model and internal and external balance training is achieved.

The invention relates to the technical field of data security situation analysis, in particular to a data security situation awareness system based on multi-level data intelligent fusion, which comprises a multi-source data center, a data preprocessing module, a processing quality unit, a demand analysis unit, a cross-domain feature fusion module, a dynamic risk awareness unit and a processing response unit. According to the method, the deep learning model is used for automatically extracting and fusing different levels of data features, the complex incidence relation between the data is effectively captured, the discrimination ability of feature representation is improved, and meanwhile, the code semantic feature, the flow space feature, the flow time sequence feature, the log feature and the user operation feature vector are integrated, so that the user experience is improved. According to the method, the limitation of a single data dimension is overcome, the security risk level is divided according to the Hamming distance D, and through visual display and an automatic response mechanism, the workload of security operation and maintenance personnel is reduced, and the accuracy and the real-time performance of security threat identification are improved.

The invention discloses an artificial intelligence-based tourism strategy automatic generation method, which belongs to the technical field of tourism strategy generation, and comprises the following steps: S1, tourism demand analysis, S2, dynamic physical strength and emotion prediction, S3, elastic scenic spot sorting and alternative generation, S4, cross-platform transaction, and S5, preference and strategy optimization. According to the method, a multi-modal model is utilized to analyze hidden information in texts, pictures and voices, for example, demands for barrier-free facilities are recognized from playing with the elderly, meanwhile, physiological data of intelligent equipment are accessed, and factors such as weather are combined to predict daily physical strength and emotion, so that the user experience is improved. The generated strategy is accurately matched with the real demand and the physical state of the user, the stroke discomfort caused by the demand understanding deviation is avoided, and the integrating degree of the playing experience of the user is improved.

The invention relates to the technical field of internet-of-things automobiles, in particular to an automobile data collecting and processing method which comprises the steps that an internet-of-things module is loaded behind a vehicle standard OBD diagnosis port, a vehicle bus data flow is collected and uploaded to a cloud background, and according to all scene requirements in the whole life cycle of a vehicle, the internet-of-things module is connected with the internet-of-things module; and calling an algorithm model to analyze, analyze and process the Internet of Vehicles data flow, actively developing user demands, analyzing user intentions to adjust data weights, and completing data interaction with a user side. According to the automobile data collecting and processing method, the control logic and the AI algorithm are fused, the threshold value judgment rule of a power assembly and a new energy electric drive assembly system is improved, the strong nonlinear fitting capability of XGBoost is combined, the real-time performance and reliability of automobile condition monitoring are improved, XGBoost-Boruta mixed feature screening is adopted, and the real-time performance and reliability of automobile condition monitoring are improved. Compared with a traditional Dropout method, the model interpretation and generalization ability are improved, a feature selection optimization strategy is achieved, and dynamic updating of a data acquisition model of a departure end under a background and millisecond-level response of background calculation are supported through incremental training and a low-delay architecture and based on a distributed data acquisition and calculation framework of the high-speed Internet of Things.

This application belongs to the field of aircraft overall design and functional structure design, and particularly relates to a structural-functional integrated thermal design method. It includes: clarifying the functional structure design boundary through requirements analysis; comprehensively considering the basic characteristics and technical feasibility of the material database, active cooling structure configuration database, and manufacturing process database, and conducting technical option demonstration under the structural geometric constraint conditions; identifying the structural flow channel design parameters and active cooling system design parameters, combining with the experiments of key parameter components, analyzing the influence laws on the structural heat transfer and heat exchange characteristics, summarizing the key parameter groups of the structural-functional integrated thermal design, and selecting the structural flow channel design parameters and active cooling system design parameters according to the action effects to complete the scheme design; hierarchically decomposing the functional structure comprehensive evaluation index system from multiple dimensions, and completing the scheme evaluation and parameter optimization design according to the evaluation requirements; completing the thermo-mechanical coupling test of typical functional structure test pieces under simulated thermal conditions.

The invention relates to the technical field of resource optimization, in particular to a laboratory resource optimal distribution system based on cloud computing and big data analysis, which comprises a resource state monitoring module, a resource demand analysis module, a resource dynamic adjustment module, a resource efficiency analysis module and a resource optimization execution module. According to the method, through time interval grouping and interval difference calculation, in combination with periodic reagent consumption trend analysis, high-demand and low-demand intervals of laboratory resources are accurately positioned, the accuracy and pertinence of resource allocation are optimized, meanwhile, excess resources are recycled and stored, and meanwhile, insufficient parts are supplemented; the conditions of excessive consumption and unused resources are concluded, the recognition and response capabilities of differences between resource allocation and actual demands are improved, resource waste or insufficient allocation caused by static allocation is reduced, and high adaptability of resource utilization is realized by optimizing the equipment starting sequence and the reagent allocation rhythm. Powerful support is provided for the continuity and the high efficiency of the experiment process.

The invention relates to the technical field of intelligent automobiles, in particular to an intelligent automobile information physical system architecture design method based on system engineering, and the method comprises the steps: carrying out the strategic analysis, operation analysis, service analysis and resource analysis of each scene task system based on a system engineering strategy, so as to design each scene task system architecture; carrying out demand analysis and context construction analysis on each member system to construct a functional logic architecture of each member system, carrying out logic simulation and information physical architecture, and carrying out parameter simulation processing to design an architecture of each member system; and based on each scene task system architecture and each member system architecture, designing a final intelligent automobile information physical system architecture. According to the method, on the basis of the IVCPS-MBSoSE method, the overall architecture of the IVCPS is maintained while the architecture of each scene task system is iteratively constructed, and benign emergence of multiple scenes is ensured through multi-resolution scene integration simulation.

The present invention discloses a visual communication design and display system based on model analysis, which relates to the technical field of visual communication design, and includes a design requirement analysis unit, a design output unit, a design display unit, a user feedback analysis unit, and a design optimization unit; the present invention identifies each natural language command through a large language model, determines the design requirements expressed by each natural language command, determines the corresponding design system, page image, and page template based on the design requirements, generates a trial-run user interface design draft and displays it to the user side, establishes a user portrait based on the user's basic information, obtains a user feature coefficient, and at the same time constructs a user behavior table based on behavior data, analyzes the user behavior table through a deep learning model, and then evaluates the trial-run simulation interface to obtain an evaluation result, and performs user interface responsive design optimization for the page module corresponding to the trial-run simulation interface to adapt to different user needs.

The invention discloses a skill grade evaluation system for talent management. The skill grade evaluation system comprises a demand analysis module, a data collection and preprocessing module, a skill mapping module, a skill level analysis module, a development path planning module and a system optimization module. The invention belongs to the technical field of human resource management, and particularly relates to a skill grade evaluation system for talent management, which is characterized in that skill data are converted into feature vectors through a data preparation unit, a Gaussian mixture model is defined, and model parameters are iteratively optimized through a parameter estimation unit; calculating the posterior probability that a new data point belongs to each skill category through the trained model, and achieving the classification of skill levels; the skill level is analyzed based on a decision tree and an entropy theory, accumulated residual entropy is calculated to evaluate the uncertainty of overall skill distribution, the influence degree of residual uncertainty analysis features on skill evaluation is calculated, and optimal features are selected according to information gains to achieve skill level evaluation.

The invention discloses a helicopter transmission system digital engineering overall technology analysis method, and relates to the field of helicopter transmission system digital engineering, and the method comprises the steps: building a helicopter transmission system overall design digital environment; demand capturing is carried out around all benefit critical people and facing scenes; obtaining preliminary design requirements, node parameters, interface requirements and overall requirements of the helicopter transmission system; carrying out helicopter transmission system-component-part demand analysis, and establishing a demand model, a function model, a logic model and a physical model; establishing a design model, a manufacturing model, an assembly model and a test model; and establishing a comprehensive database, and storing the model established in each stage into the comprehensive database to realize numerical model multiplexing and complete digital design closed loop. The problems that a traditional analysis method is low in efficiency, low in integration level, short in simulation evaluation and long in closed loop iteration period are solved.

The invention provides a product configuration method based on aero-engine unit body modularization, and belongs to the technical field of aero-engines, the method comprises the steps that an aero-engine is divided into a plurality of unit bodies based on demand analysis, and each unit body comprises a plurality of configuration schemes; for each unit body, acquiring attribute information of each configuration scheme, and judging whether the configuration scheme conforms to a preset unit body storage criterion or not based on the attribute information; based on the conformed configuration schemes and the corresponding attribute information, a unit module database is constructed, and each configuration scheme corresponds to one unit module; determining a target unit body and a corresponding design requirement based on a new product target demand; and based on the unit module database, performing configuration combination of each unit module meeting the target unit design requirements, and performing optimization on the configuration combination based on the unit values of the unit modules to obtain a final complete product design scheme. The design cost can be reduced, the product maturation period is shortened, and rapid series development and derived development of products are supported.

The invention discloses an intelligent demand analysis and man-hour evaluation method and system, and belongs to the technical field of computer vision and artificial intelligence. Analyzing the multi-modal demand document containing the text, the picture and the table to generate structured demand data; based on the structured demand data and the system module description, performing module-level splitting on the demand to generate a module task set; retrieving an associated system implementation context for each task in the module task set based on a multi-dimensional knowledge base; fusing the structured demand data, the module task set and the system implementation context to generate a fine-grained technical task; based on a historical case index, calculating reference working hours for the fine-grained technical task; and cross-module cooperative correction and personalized correction based on the ability of the task executor are sequentially performed on the reference working hours to obtain final evaluation working hours, so that automatic deep analysis and accurate and personalized working hour evaluation of software requirements can be realized.