278 results about "Assessment data" patented technology

The invention relates to the technical field of data acquisition, and discloses a multi-protocol extensible data acquisition system architecture and method with a unified interface standard, and the architecture comprises a data source management module which is used for storing data source configuration information and distributing protocol identifiers; the protocol adaptation module comprises an analysis unit and a matching unit and is used for realizing data format conversion and protocol compatibility verification; the data conversion module is used for generating target data through format conversion and semantic mapping; the data verification module and the anomaly detection module are used for comparing and monitoring data integrity based on an integrity algorithm and a threshold value; the data quality monitoring module and the early warning module are used for comparing and evaluating data quality through a consistency model and a threshold value; and the result output module transmits the early warning information to a target system. The method comprises the steps of data source configuration, protocol adaptation, data conversion, integrity and quality monitoring, early warning and the like. The system expansibility and the data reliability are improved, and the method is suitable for multi-scene data acquisition.

The invention relates to the technical field of water and fertilizer control, in particular to a water and fertilizer integrated control system and method based on the Internet of Things. The method comprises the following steps of obtaining environment measured data, historical environment data and regional geographic information of a farmland region, performing spatial modeling and time sequence learning on the farmland region, and constructing a farmland digital twinborn model; simulating the state of an area without sensors by using a farmland digital twinborn model to obtain virtual sensing node data; collecting multispectral image data of crops, and extracting physiological feature data of the crops; and constructing a crop physiological state model by utilizing the environment measured data, the virtual sensing node data and the crop physiological feature data, and generating crop physiological state evaluation data. Through multi-source data fusion and three-dimensional visualization integration, data-driven accurate regulation and control and whole-process intelligent management of the water and fertilizer integrated system are realized, and the intelligent level of irrigation and fertilization and the resource utilization efficiency are comprehensively improved.

The invention relates to the technical field of power equipment monitoring, and discloses a hydropower station high-altitude equipment fault intelligent identification system based on multi-sensor fusion, which collects multi-modal data in real time and evaluates data quality by deploying multi-source sensors at key parts of high-altitude equipment. Extracting multi-scale features of each modal, performing normalization processing, calculating a fusion weight based on feature saliency and data credibility, and performing weighted fusion and dimension reduction on the multi-modal features; based on the fusion feature vector, intelligent matching analysis of fault features and intelligent identification of fault types are carried out; a fault identification result is obtained; in addition, the system also comprises safety monitoring of overhead working personnel, and realizes closed-loop management from fault identification to safety maintenance. According to the invention, early weak faults can be accurately identified, and the safe operation level of equipment and the intelligent degree of operation safety management are improved.

The invention discloses a multifunctional safety helmet management system and method based on the Internet of Things, relates to the field of safety production, and solves the problems that a traditional safety helmet is single in safety management function, insufficient in data processing precision and the like. A multi-dimensional state data sequence is continuously collected through a three-axis acceleration sensor, a temperature and humidity sensor, a positioning sensor, a vital sign sensor and the like integrated on the safety helmet terminal; terminal monitoring characteristics including an acceleration module value, a position drift distance and a physical sign fluctuation index are constructed, data reliability is evaluated through weighted fusion of dynamic fluctuation values, and an abnormal terminal is isolated. And carrying out space-time calibration on the reliable data to generate a unified coordinate system trajectory, analyzing and identifying abnormal behaviors through group trajectory consistency, and constructing a regional safety risk map in combination with a signal blind area coverage rate, thereby realizing safety risk level prediction based on historical data and real-time trajectory matching. According to the invention, comprehensive real-time monitoring of the state of the operator is realized, and the intelligent level of safety production management is improved.

The invention discloses a BIM application method and system in cost management. The method comprises the steps of BIM model construction, cost data integration, engineering quantity list and cost report generation, collaborative management, AI real-time optimization, digital twinborn early warning management, design change and contract text analysis, edge calculation cost management, block chain data guarantee and the like. The system comprises a plurality of modules such as a BIM model construction module and a cost data integration module. According to the method, software is utilized to generate a BIM model, cost data is integrated, data quality is evaluated before a report is generated, multi-specialty and multi-participant authority is cooperatively managed, AI real-time optimization, digital twinborn early warning, a natural language processing engine analyzes a change document, cost is processed through edge calculation, safety protection is achieved, and data is guaranteed in combination with a block chain. Compared with the prior art, the construction cost calculation accuracy is improved, personal errors are reduced, the association between the component and the construction cost data is enhanced, the change response efficiency is improved, and the data transmission delay is reduced.

The invention discloses a course recommendation method and system for intelligently building an education platform, and relates to the technical field of intelligent education informatization, and the method comprises the steps: building a knowledge graph, and completing the multi-level association of tasks and knowledge points; analyzing the assessment data, identifying weak knowledge points of the trainees, and setting score threshold fusion post weights; generating a course recommendation result on the basis of recognizing weak knowledge points of students, and optimizing recommendation logic in real time by adopting feedback; according to the method, a knowledge graph model associated with three layers of tasks, knowledge points and posts is constructed, student examination performance and post skill requirements are fused, and a course recommendation path construction mechanism driven by a multi-dimensional weight is realized; a dynamic feedback and real-time scoring algorithm is adopted, closed-loop logic of recommendation, assessment and re-recommendation is established, recommendation individuation and post matching degree are effectively improved, and the problems that knowledge points in an existing platform are not traceable, post adaptability is weak, and a recommendation strategy is single are solved.

The invention relates to the technical field of training simulation, and discloses a VR-based gas safety emergency training system, which comprises a three-dimensional scene construction module, an interactive data acquisition module, an interactive data processing module, an examination data analysis module and an examination evaluation module, entity drilling is replaced, the same scene can be repeatedly trained for infinite times, and the training cost is remarkably reduced; the VR technology provides multi-sensory stimulation, the intuitive cognition of students on danger is enhanced, the safety awareness and the emergency response capability are effectively improved, and no danger exists; by collecting operation data of students, the system automatically calculates key coefficients such as equipment operation precision, process compliance, disposal timeliness and path planning rationality, and scientific quantification and accurate scoring of training effects are achieved; and automatic grading evaluation is carried out according to a grading result, and a customized remedy module is triggered for students with insufficient abilities, so that a'training-assessment-intervention 'closed loop is formed, and the overall training efficiency is improved.

The invention discloses a BIM-based bridge construction monitoring method and system, and belongs to the technical field of bridge construction. Construction time deviation characteristics and structure response deviation characteristics are extracted, a drift index is calculated to evaluate the binding error degree between data and components, and a differential processing strategy is implemented based on the drift level; and for high-risk data, a similarity scoring mechanism is introduced, an intelligent matching algorithm is adopted to identify an optimal component and complete rebinding, and finally accurate storage of the data and dynamic updating of a BIM model state are realized, so that the binding accuracy of the construction monitoring data, the risk identification capability and the model linkage efficiency are effectively improved, and the construction quality is improved. And the intelligent management and decision support level of bridge construction is enhanced.

The invention discloses a water feed pump fault diagnosis system, which belongs to the field of data analysis and is characterized in that real-time operation data of a water feed pump are acquired by adopting a synchronous acquisition strategy, an operation database is constructed, and when a data record is newly added, detection and self-adaptive judgment are performed to determine an early warning decision; when abnormal early warning of the water feeding pump is detected, screening a fault assessment set for fault identification based on the operation database, and performing information fusion on fault assessment data to obtain a fault assessment feature set; and performing comprehensive time sequence analysis on the preliminary fusion data of each fault evaluation subset to obtain a key part fault evaluation score so as to judge a fault, for the key part judged as the fault, obtaining a fault source by constructing a time axis, and constructing a fault propagation path in combination with a correlation coefficient matrix. The technical problems of synchronization and exception handling during collection of multi-source information, targeted screening and effective integration during fusion, and discrimination and traceability during fault diagnosis are solved.

A system, method, and computer programmable product for assessing a virtual interaction is provided. The system is configured to retrieve assessment data, wherein the assessment data comprises at least one of: a plurality of assessment parameters, and a weightage score associated with each of the plurality of assessment parameters. The system is further configured to retrieve response data of a candidate associated with the assessment data. The system is configured to generate, using a trained AI model, a score for the response data based on the assessment data. Further, the system is configured to obtain user input based at least on the score of the response data and update the weightage score associated with at least one of the plurality of assessment parameters based on the user input, wherein the AI model is re-trained based on the updated weightage score.

The invention discloses a black land water and soil resource bearing capacity evaluation system based on big data, which relates to the technical field of agricultural production and comprises a data acquisition module, a data preprocessing module, an evaluation index calculation module, a bearing capacity evaluation model module and a result analysis and display module. The data acquisition module is used for acquiring soil data, water resource data and social economic data of black land. According to the evaluation system for the bearing capacity of the water and soil resources of the black land, through integration of multi-source heterogeneous data, comprehensive and accurate evaluation of the bearing capacity of the water and soil resources of the black land is achieved, high-density deployment and real-time updating of the data acquisition module are achieved, the temporal-spatial resolution and reliability of an evaluation result are ensured, and the evaluation accuracy is improved. The problem of insufficient data acquisition density in the prior art is effectively solved, a data preprocessing and evaluation model construction technology is adopted, the dynamic adaptability and prediction precision of an evaluation model are improved, and visual and understandable chart display and decision support information are provided.

The invention relates to a wound nursing image intelligent evaluation system and a method thereof, which are applied to the field of medical image processing, and comprise an image acquisition module, a differential geometry-based feature extraction network module, a data analysis module and a user interaction module, the feature extraction network module based on differential geometry comprises a wound geometric characterization layer, a multi-scale feature analysis layer and a tissue classification decision-making layer, a two-dimensional image of the wound is mapped into a three-dimensional geometric surface, curvature features and differential invariants are extracted based on the differential geometry theory, accurate assessment of the wound is achieved, and the tissue classification decision-making efficiency is improved. The data analysis module generates nursing suggestions and evaluation results according to the extracted wound feature data, the differential geometry theory is innovatively applied to the field of wound evaluation, and the problem that the precision is limited when a traditional method is used for treating a wound with a complex shape and irregular edges is effectively solved; the system has the characteristics of high evaluation accuracy, strong anti-interference capability and high automation degree, and the efficiency and quality of wound evaluation and nursing are remarkably improved.

The invention discloses a data value evaluation method based on a data blood relationship, and relates to the technical field of data processing. The method comprises the following steps: constructing data blood relationship map data based on sensor metadata, communication protocol characteristics and a data blood relationship; obtaining a data value dynamic sorting result; constructing a monitoring index, importing the monitoring index into a tool to configure a data quality automatic monitoring tool, and obtaining a data exception intelligent detection result of the focused data node by using the data quality automatic monitoring tool; and performing data error repair and data processing flow optimization by using the block chain consensus and generative adversarial network to obtain a final data value evaluation result. According to the method, the data blood relationship graph can be efficiently constructed, the data value can be evaluated, the data quality can be monitored, and the data management strategy can be optimized, so that more accurate and reliable data support can be provided for decision making in intelligent traffic.

Described herein are methods and systems for evaluating datasets through a multi-faceted scoring approach that assesses data quality across multiple dimensions. A trust score for a dataset may be generated by a scoring engine and displayed on a user interface, providing a comprehensive assessment of the dataset's readiness for use in artificial intelligence applications. The trust score incorporates multiple dimensions including diversity, timeliness, accuracy, security, discoverability, and LLM-readiness, offering users quantitative insights into dataset quality. This scoring system enables organizations to identify high-quality datasets suitable for AI model training, reducing the risk of poor model performance due to inadequate data. The visualization of trust scores through intuitive interfaces allows data scientists, analysts, and other stakeholders to quickly assess and compare datasets, facilitating more informed decision-making in AI development processes.

The invention relates to the technical field of data processing, and discloses a full-life-cycle-oriented engineering technology data governance method and a full-life-cycle-oriented engineering technology data governance system. The method comprises the steps that project object attributes are divided into an anchor point attribute set and an extended attribute set, a locking mark is added to the anchor point attribute set, the extended attribute set is layered according to stages to obtain a data object meta-model, a dependency relationship mapping table is established according to the data object meta-model to achieve automatic verification when the attributes are changed, and the attribute change is completed. And establishing a spatial topological graph and a process graph to diagnose inconsistent defects, establishing a weighted graph to quantitatively analyze change influences, evaluating data quality according to scene types, and intelligently complementing missing attributes. According to the method, the integrity and consistency of cross-stage transmission of engineering data, the real-time performance and accuracy of multi-professional data collaboration, the depth and automation degree of data quality diagnosis, the scientificity and comprehensiveness of change impact analysis and the flexibility and efficiency of data utilization are improved.

The invention relates to the technical field of data management, and discloses a business and financial data governance optimization method for main data dynamic management, which comprises the following steps: step 1, carrying out multi-source data acquisition, including business system data acquisition, financial system data acquisition and other channel data acquisition, step 2, pre-processing the acquired data, numbering and storing, and step 3, carrying out data management on the acquired data. 3, calculating a data quality index, a data change condition, a data value and a data comprehensive coefficient based on the stored data set, and 4, performing feedback according to the data comprehensive coefficient, so that various data sources inside and outside an enterprise can be comprehensively covered, a data island phenomenon is reduced, and meanwhile, the quality and credibility of data are improved; the data comprehensive coefficient is comprehensively evaluated by combining the data quality index, the data change condition and the data value, the data level is comprehensively reflected, a comprehensive perspective is provided for enterprises to see the data, and the enterprises can better understand and manage the data and find potential problems and opportunities.

The invention relates to the technical field of intelligent teaching, and provides a self-adaptive personalized teaching system based on AI and a knowledge graph, and the system comprises a knowledge graph construction module, a student portrait module, a self-adaptive recommendation module, a teaching interaction module, and a management module. The knowledge graph construction module comprises a data processing unit, a knowledge extraction unit and a graph storage unit; the data processing unit is used for carrying out preprocessing such as word segmentation and stop word removal on the teaching text; and the knowledge extraction unit is used for extracting knowledge point entities and relationships between the entities from the preprocessed text through a natural language processing technology. The knowledge points are subjected to fine-grained modeling through the knowledge graph, the AI algorithm is combined to analyze student learning behaviors and evaluation data, knowledge vulnerabilities and learning characteristics of students can be accurately captured, the error rate is lower than that of a traditional method, the self-adaptive recommendation module generates personalized learning paths based on the reinforcement learning algorithm, and the learning efficiency is improved. And repeated learning of students on invalid knowledge points is avoided.

The invention relates to the technical field of engineering digital management, in particular to an engineering project digital asset management method and management platform. The method comprises the following steps: performing engineering digital asset quality evaluation processing on engineering digital asset data to generate engineering digital asset quality evaluation data; performing engineering digital asset collaborative application heterogeneity feature analysis based on the historical engineering digital asset application data to generate engineering digital asset collaborative application heterogeneity feature data; carrying out the optimal distribution strategy analysis of the full-life-cycle engineering digital asset application on the full-life-cycle engineering digital asset application data through the engineering digital asset collaborative application heterogeneity feature data, and generating a full-life-cycle engineering digital asset application optimal distribution strategy; and based on the engineering digital asset quality data and full-life-cycle engineering digital assets, applying an optimal distribution strategy to execute engineering digital asset intelligent management operation. According to the invention, intelligent operation and maintenance optimization management of engineering project digital assets is realized.

The invention relates to a scene-based data asset evaluation method and system. The method comprises the following steps: step 1, evaluating a scene in which data assets can be used; 2, calculating the contribution degree of a single determined scene; 3, single evaluation is carried out to determine the number of scenes; 4, calculating a scene correction coefficient; 5, evaluating a data asset value; according to the method, evaluation is carried out by adopting the scene number, the scene contribution degree and the correction coefficient, the requirements and evaluation of a cost method, a benefit method and a market method for data quality are reduced, the core of data asset evaluation is powerfully grasped, and an accurate and reliable basis is provided for data asset evaluation.

The invention relates to the technical field of medical informatization, in particular to an intelligent rehabilitation assessment and data analysis method and system.The method comprises the steps that multi-source heterogeneous rehabilitation assessment data collected by a wearable sensor when a patient executes a preset rehabilitation action is obtained in real time; based on a preset time window, processing the multi-source heterogeneous rehabilitation evaluation data into a series of time sequence dynamic graphs; inputting the series of time sequence dynamic graphs into a pre-trained time sequence dynamic graph neural network model, and generating a quantized rehabilitation evaluation result based on the output of the time sequence dynamic graph neural network model. According to the method, deep fusion and time sequence calibration of the multi-source heterogeneous rehabilitation data are realized, the precision of an evaluation model and the recognition capability of a complex motion mode are remarkably improved, the robustness of the model to noise and data artifacts is enhanced through adaptive weighting of the data quality, and the accuracy of the evaluation model is improved. And the reliability and the stability of a rehabilitation evaluation result in a real clinical environment are ensured.

The invention belongs to the technical field of information fusion, and discloses a satellite and low-altitude facility data fusion method based on a space-time self-calibration module, a hierarchical feature compression module and a dynamic weight feedback module. GNSS original acquisition data and low-altitude facility data are sent into the space-time self-calibration module, and the space-time self-calibration module automatically constructs a cross-source space-time reference based on feature matching; the layered feature compression module performs bidirectional feature distillation on a feature layer, and compresses data dimensions while reserving complementary information; the dynamic weight feedback module constructs a double-loop feedback mechanism, evaluates data quality in real time and adjusts a fusion strategy, the double-loop feedback mechanism of the dynamic weight feedback module comprises feature weight feedback and confidence feedback, the feature weight feedback dynamically adjusts fusion weight, and the confidence feedback evaluates low-altitude facility data quality; and outputting a fusion result.

The invention relates to the technical field of big data analysis, and particularly discloses a city update multi-dimensional dynamic supervision and analysis system based on big data, which is provided with a data quality processing module, a topology verification evaluation module, a conflict repair matching module and an interactive management feedback module. And extracting data from the city multi-source data set and performing coordinate conversion to form a unified city space data set. And then, starting a topology check engine through a data processing port, and detecting and evaluating a topology conflict degree value of the data set. And according to the conflict degree, matching and executing a corresponding repair scheme, and marking the repaired data set as a city effective data set. And finally, the effective data set is uploaded to a city updating interaction port, subsequent interaction management operation is carried out, the accuracy and availability of the data are ensured, and support is provided for a city updating project.

The invention discloses a livestock and poultry product full-chain traceability and slaughter supervision system based on a block chain, and belongs to the technical field of food safety traceability, and the system comprises a multi-source data fusion collection module, a block chain intelligent evidence storage module, an intelligent contract supervision module and a traceability credibility verification module. The multi-source data fusion acquisition module integrates RFID, IoT and video AI technologies to acquire full-dimensional traceability data and evaluate data quality, and the block chain intelligent evidence storage module adopts an alliance chain and an improved Hash algorithm to realize data credible evidence storage and dynamically adjust consensus weight. The intelligent contract supervision module automatically executes compliance check and generates a supervision adjustment instruction to form closed-loop feedback, the traceability credibility verification module adopts deep learning to perform authenticity verification and calculate a comprehensive risk score, and the four modules realize mutual promotion and superimposed synergy through a deep coupling closed-loop cooperation mechanism. And the efficiency and reliability of food safety supervision are obviously improved.

The invention relates to the technical field of data processing, can be applied to the field of science and technology finance, and discloses a credit evaluation method and device for multi-source data co-processing and related equipment. The method comprises the steps of receiving credit evaluation data of at least two types of preset data sources, and performing cleaning, time scale unification and numerical standardization processing on the credit evaluation data to form standardized multi-source feature data; constructing credit portrait data based on the standardized multi-source feature data; performing scoring reasoning on the credit portrait data through a pre-trained credit extension evaluation model, and generating credit extension evaluation result data through a limit mapping rule; receiving the use behavior data and the performance behavior data, performing time sequence analysis and deviation identification, and generating credit use behavior analysis data; and updating credit extension evaluation model parameters based on the credit use behavior analysis data, loading the credit extension evaluation model parameters to a model operation state, outputting credit extension evaluation result data, and recording model parameter updating information. According to the method, the dynamic adaptive capacity of multi-source credit assessment is improved.

The invention discloses a dam interior and exterior deformation monitoring method and system based on deep fusion of finite element and GNSS (Global Navigation Satellite System) monitoring. According to the method, surface displacement observation data are obtained through a GNSS receiver, a finite element model is constructed, and the mechanical response of the finite element model under hydrostatic pressure, temperature and seismic load is simulated. According to the first layer, parallel primary fusion is conducted on GNSS data and finite element output through Kalman filtering, particle filtering, a neural network and a Bayesian algorithm; in the second layer, weights are dynamically distributed on the basis of mean square errors of all algorithm results in a sliding window and reference data, and a high-precision displacement estimation value is generated through weighted integration. The system evaluates data quality and model confidence in real time, dynamically optimizes weight distribution, performs early warning based on multistage thresholds of displacement, speed and acceleration, and finally studies and judges structural risks through time sequence decomposition and abnormal mode recognition. According to the invention, the overall precision and reliability of dam deformation monitoring are significantly improved.

The invention discloses a health risk assessment method and system based on multi-source data fusion analysis, and belongs to the technical field of health risk assessment, and the method comprises the steps: S1, obtaining the physiological data and behavior data of a user in real time, and generating a multi-source data stream; s2, monitoring the multi-source data flow in real time by a preset terminal, and generating a first health assessment data set and a second health assessment data set; s3, performing dynamic analysis based on the first health assessment data set or the second health assessment data set to generate a health risk level; s4, generating an early warning signal based on the health risk level, and transmitting the early warning signal to preset user equipment; and S5, comparing the subsequently acquired multi-source data stream with the virtual data stream generated in the historical monitoring time period, and dynamically adjusting the parameters of the healthy digital mirror image model. The system comprises an acquisition module, a generation module, an analysis module, an early warning module and an optimization module. According to the method, the virtual data stream is generated in combination with the historical multi-source data stream, so that the integrity of health risk assessment is improved.

The invention belongs to the technical field of water affair management, and discloses an intelligent water affair dynamic monitoring system and monitoring method based on digital twinning. Comprising the steps of collecting multi-modal water affair data in a preset water affair system and performing data cleaning to obtain standard multi-modal water affair data; adaptive weighted fusion is carried out on the standard multi-modal water affair data, and a multi-modal water affair data matrix is constructed; constructing a digital twin water affair architecture and constructing a simulated water affair management scene; constructing an ecological evaluation model to perform water quality monitoring on the simulated water affair management scene, and outputting water quality evaluation data; constructing a water affair management partition topological structure to perform water resource cross-region scheduling on the simulated water affair management scene, and outputting a water affair partition management strategy; constructing a water affair system assembly operation scene to carry out system fault monitoring, and outputting a system maintenance log; collecting real-time water affair data and combining with a system maintenance log to perform parameter updating on the digital twin water affair architecture to obtain an optimized digital twin water affair architecture; and efficient water affair management is realized.

The invention discloses a talent evaluation and post matching system and method, and relates to the technical field of information, and the system comprises a personality evaluation module, a post personality demand modeling module, a matching calculation module, a feedback optimization module and a data storage module. The personality evaluation module is used for acquiring a nine-dimensional personality feature vector of an employee based on a nine-type personality theory; the post personality demand modeling module is used for constructing and storing a nine-type personality weight vector model of a post; the matching calculation module calculates matching degree scores between the employees and the posts and generates a recommendation sequence based on a rule algorithm and a K-nearest neighbor algorithm; a feedback optimization module collects performance feedback data after employees enter the job, and automatically updates a matching model to improve prediction accuracy; and the data storage module is used for centrally managing evaluation data, post models and feedback records. According to the method, personalized matching and dynamic optimization between the employees and the posts are realized, and the organization configuration efficiency and the man-post adaptation quality can be improved.

The present application provides a method for assessing the value of data assets. The method is applied to a scenario where a commercial bank performs service recommendation or service delivery. The method comprises: acquiring data asset data to be assessed inputted by a user, said data asset data comprising data assets to be assessed and an association relationship between said data assets, and said data assets comprising a plurality of data table assets; generating a corresponding data asset graph on the basis of said data asset data; determining an assessment indicator for said data assets on the basis of the data asset graph, the assessment indicator comprising at least one of the following indicators: an information content indicator for the data table assets, a data transmission efficiency indicator for the data table assets, and a data flow impact indicator for the data table assets; and determining the respective value of the plurality of data table assets on the basis of the assessment indicator for said data assets. The present solution can improve the accuracy of assessing the value of data assets.

The invention relates to the technical field of artificial intelligence and vehicle crossing, and provides a commercial vehicle maintenance strategy recommendation method and system.The method comprises the steps that multi-source loss assessment data are obtained, and the multi-source loss assessment data at least comprise damage information and vehicle attributes; generating a maintenance item list based on the damage information and the vehicle attributes, and inputting the multi-source loss assessment data and the maintenance item list into a reinforcement learning model, so that the reinforcement learning model constructs a state space, defines an action space, calculates a multi-target reward function, and generates a plurality of maintenance strategies; each maintenance strategy comprises maintenance action details and corresponding multi-dimensional quantitative indexes. According to the method, multi-source loss assessment data and a maintenance item list are processed through a reinforcement learning model, and a plurality of maintenance strategies including maintenance action details and multi-dimensional quantitative indexes are generated, so that the problems that an output scheme is single, the intelligent effect is poor, and a scheme conforming to an actual maintenance scene is difficult to generate are solved.