323 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 relates to an AI-driven document data structured storage and retrieval method, which comprises the following steps of: analyzing and understanding document contents by utilizing a natural language processing technology, extracting structured question and answer knowledge, and constructing a structured question and answer knowledge base; a natural language processing technology and a large pre-training language model are utilized to analyze and understand a query request and a historical dialogue of a user, real intentions and demands of the user are extracted, and structured demand data are generated; and according to the user input and the demand analysis result, vectorizing the user input by using the pre-training language model, extracting related information from the vector database through a dynamic retrieval strategy, and generating and outputting a final answer. According to the method, deep analysis is performed on the document through a natural language processing technology, structured question and answer knowledge is extracted, and the performance and user experience of a question and answer system are improved by utilizing the semantic understanding ability of a large model.

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 provides a software demand analysis method which can be applied to the field of artificial intelligence. The method comprises the steps that demand information of target software is collected in a multi-modal mode, and initial data of m modals are obtained; wherein m is a positive integer greater than 1; based on the initial data of the m modalities, performing multi-modal demand analysis by using a first large language model to obtain information data of the m modalities; performing information fusion on the information data of the m modes to obtain software demand data; and performing demand optimization processing on the software demand data to obtain a software demand document corresponding to the target software. According to the software demand analysis method and device, intelligent demand analysis and automatic and intelligent processing of the target software are achieved, manual intervention is reduced, the processing efficiency is improved, and the invention further provides a software demand analysis device and device, a storage medium and a program product.

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 relates to a rendering adjustment method of a three-dimensional model, a rendering adjustment method of a medical three-dimensional model and computer equipment, relates to the technical field of medical models, and can efficiently meet personalized medical model rendering requirements of users. The method comprises the steps of obtaining a dialogue statement input by a user for a target three-dimensional model; the target three-dimensional model is a three-dimensional reconstruction model pre-constructed for a target organization area, and the dialogue statement is a demand statement input by the user for indicating to adjust the rendering effect of the target three-dimensional model; performing demand analysis on the dialogue statement based on a trained language model to obtain a corresponding demand instruction; the demand analysis is used for analyzing a demand description and a context in the dialogue statement so as to automatically generate a corresponding demand instruction; and based on the demand instruction, adjusting rendering parameters of the target three-dimensional model so as to display the target three-dimensional model based on the adjusted rendering parameters.

The invention provides a dynamic obstacle avoidance method and system for a sensing robot, and relates to the technical field of robot obstacle avoidance, and the method comprises the steps: obtaining a historical cleaning record; performing cleaning demand analysis, and dividing the target parking lot into a plurality of cleaning subareas; a plurality of sensing robots are configured; interactively obtaining real-time parking information, and constructing a plurality of static obstacle maps; performing cleaning route fitting according to the plurality of cleaning cycle configurations and the plurality of sensing robots; and in the process of controlling the multiple sensing robots to execute the cleaning tasks of the multiple cleaning subareas, the dynamic obstacles are recognized in real time, and dynamic obstacle avoidance optimization is conducted on the multiple standard obstacle avoidance cleaning tracks. According to the invention, the technical problem that the cleaning efficiency of the parking lot is further affected due to the delay of obstacle identification and path planning caused by the high change frequency of the dynamic obstacle in the prior art can be solved, and the automation and management efficiency of the parking lot is improved and the environment of the parking lot is optimized through real-time sensing and dynamic obstacle avoidance.

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 discloses an enterprise data intelligent analysis system based on deep learning, which relates to the technical field of data analysis, and realizes real-time acquisition and transmission of data through a data acquisition and processing module, division of department areas and integration of a staff performance system, a training system and an attendance system through multiple APIs (Application Program Interface); the effective data analysis module analyzes performance data and calculates a performance index Jxzs, the loss prediction analysis module predicts employee loss in combination with historical demission data and a performance evaluation result, the recruitment demand analysis module predicts recruitment demands in advance and calculates a recruitment demand index Zpzs, and the learning model optimization module optimizes a model and updates a data set. The real-time performance and the accuracy of the model are ensured; the system evaluates each index by presetting a plurality of thresholds, generates a corresponding evaluation result and proposes improvement measures, thereby effectively reducing the employee loss risk, and improving the recruitment efficiency and employee satisfaction.

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 provides a distributed data storage and access software development method based on cloud computing, and aims to construct an efficient, safe and extensible data storage system. The method comprises seven key steps of demand analysis and system design, cloud resource configuration and initialization, distributed data storage algorithm development, data processing layer construction, access control layer development, user interface and interaction design and system test and optimization. By accurately calculating storage resource requirements, optimizing cloud resource configuration and designing a consistent Hash data fragmentation algorithm and a data redundancy strategy, high availability and fault tolerance of data are ensured. Meanwhile, the AES-256 encryption technology and the LZ4 compression technology are adopted to guarantee the data security and the transmission efficiency. According to the method disclosed by the invention, a high-performance, extensible, safe and reliable distributed data storage and access system can be constructed, so that the increasing data storage and access requirements are met, and the user experience is improved.

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 particularly relates to a method for generating Prompt based on large language model low-code programming. According to the method for generating the Prompt based on the large language model low-code programming, a Prompt overall framework is constructed according to the function requirement and the performance requirement of a project, and the Prompt overall framework is subdivided into four parts including a role, a requirement, a standard and a result; complementing and optimizing the content of the Prompt framework, and adding more detailed information capability description; and optimizing the generated Prompt, and continuously adjusting and perfecting the content according to the output result feedback of the large language model until the quality evaluation index and the effect verification index both reach self-defined threshold values so as to meet the project requirements. According to the method for generating Prompt through low-code programming based on the large language model, intelligentization and high efficiency of programming and document generation are achieved, flexibility is high, the programming output dimension is greatly enriched, the overall period of a project from demand analysis to test release is shortened, and the method has extremely high practical value.

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 relates to the technical field of customer management, in particular to a cross-channel customer interaction management system and method based on data fusion. The method comprises the following steps: acquiring a customer communication demand, analyzing the customer communication demand, and determining customer basic information and customer communication content; based on multi-channel data, according to the basic information of the customer and the communication content of the customer, determining a consultation intention of the customer; and determining a reply thought according to the customer consultation intention, and responding to the customer according to a preset reply logic and the reply thought. User requirements are quickly responded, and the waiting time of customers is shortened. The personalized service is based on multi-channel data and communication history of the customer, and can provide services better meeting customer requirements, thereby improving customer satisfaction. And by utilizing machine learning and natural language processing technologies, the system can more accurately identify the consultation intention of the customer, and misunderstanding and repeated consultation are reduced. The accuracy of consultation response is improved, and the customer is ensured to obtain correct information and suggestions.

The invention discloses an FPSO (floating production storage and offloading) riser support structure modeling method, which belongs to the field of simulation modeling and comprises the following specific steps: I, acquiring basic parameters through data acquisition equipment and field experiments, and analyzing an application scene and working conditions of an FPSO riser support to determine modeling requirements; iI, on the basis of a demand analysis result, constructing a preliminary stand pipe supporting structure model of the stand pipe supporting structure; according to the method, design and operation decisions can be dynamically adjusted, long-term benefits are optimized, it is ensured that the structure can keep high reliability and benefits in the long-term operation process, and the flexibility and adaptability of structural design and maintenance schemes can be improved; the safety and privacy of the method are enhanced, real-time adaptation to the multi-field coupling effect in long-term operation is achieved, the performance of the riser supporting structure can be improved from different angles, the calculation cost is reduced, the calculation efficiency is improved, and delay possibly caused by concentrated calculation is avoided.

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 a dynamic simulation cooperative regulation and control method for an urban water system. Comprising the following steps of demand analysis and target setting, data collection and analysis, modeling and simulation, simulation analysis and verification, collaborative regulation and control strategy making, implementation and monitoring, and evaluation and improvement. In a demand analysis and target setting stage, key problems are identified through investigation and research, and water-saving, energy-saving and carbon emission reduction targets are set. In the data collection and analysis stage, data of water resources, energy consumption and carbon emission are collected, processed and analyzed. In the modeling and simulation stage, multi-agent modeling and system dynamics modeling are adopted, and an urban water system dynamic simulation platform is constructed. In the simulation analysis and verification stage, simulation models under different scenes are operated, the accuracy and reliability of the models are verified, the simulation models and regulation and control strategies are optimized, efficient utilization of urban water resources is achieved, energy consumption and carbon emission are reduced, and sustainable development of the urban ecological environment and social economy is promoted.

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 safety protection, and discloses a system for realizing password resetting automation through an RPA technology, and the system comprises a demand analysis module which is used for analyzing and understanding an existing password resetting process, and determining the applicability and optimization point of application RPA; the flow design module is used for designing an automatic processing flow and rule and ensuring the safety and accuracy of the flow; the technology type selection module is used for selecting proper RPA robot software and engine and determining development and implementation schemes; the development environment building module is used for configuring a development environment and preparing software and hardware facilities required by development; through the developed RPA robot, preset automatic tasks can be continuously executed in an all-weather mode, the manual operation time is greatly shortened, and therefore the working efficiency is remarkably improved. By means of the automatic processing, a large amount of repeated and tedious work can be rapidly completed, and workers can concentrate on more valuable work.