331 results about "Analytic hierarchy process" patented technology

The invention discloses a project performance evaluation and risk early warning method for multi-source heterogeneous scientific research data, and relates to the technical field of scientific research project management, and the method comprises the steps: collecting the multi-source heterogeneous scientific research data, cleaning, converting, filling missing values, and storing in a unified format; extracting performance and risk features, and fusing to obtain a fused feature set; combining an analytic hierarchy process, an entropy weight method and the like to construct a dynamic weight performance evaluation model; constructing a multi-modal risk early warning model by adopting multiple algorithms and optimizing a threshold value; collecting data in real time to update a feature set, and dynamically adjusting the model; and visually outputting a result, generating an improvement suggestion, and forming closed-loop feedback. According to the method, the multi-source data processing efficiency and evaluation accuracy are improved, the risk early warning timeliness and adaptability are enhanced, a management closed loop is formed, and the problems of difficult data integration, evaluation lagging, insufficient early warning and the like of a traditional method are solved.

The invention discloses a data and knowledge dual-drive wheel set multi-parameter comprehensive state evaluation method and system, and belongs to the technical field of railway vehicle maintenance. The method comprises the following steps: firstly, constructing a mapping relation between geometric parameters and dynamic performance indexes through sampling and dynamic simulation, and carrying out global sensitivity analysis to screen key dynamic performance indexes; secondly, determining subjective and objective weights of the indexes in combination with an analytic hierarchy process and an entropy weight method, and introducing a dynamic optimization model based on a Bellman equation to generate a final combined weight; then, constructing a multi-dimensional state space division model by applying adaptive kernel density estimation and fuzzy C-means clustering, and determining the probability density and membership function of each index under different health levels; and finally, performing simulation prediction on the target wheel set, inputting a predicted value into the state space model, fusing a dynamic combination weight and a D-S evidence theory, calculating a comprehensive health index, and outputting a grading result, so that the health state of the wheel set can be accurately and efficiently evaluated.

The invention belongs to the technical field of virtual power plants, and particularly relates to a virtual power plant resource aggregation method for a dynamic peak regulation demand of a power grid, which comprises the following steps of: acquiring multi-source data, preprocessing the multi-source data, and then verifying the data quality; aiming at different resource types including temperature control load, energy storage and charging piles, respectively constructing refined models, setting constraint conditions of the refined models, and solving a resource operation feasible region by applying multi-dimensional space mapping and linear programming; establishing a target function and a constraint condition by taking the lowest cost and the minimum energy abandoning as targets; solving a target function by using a dung beetle optimization algorithm, and screening an optimal resource aggregation scheme by using an entropy weight method; and based on the optimal resource aggregation scheme, dividing peak, valley and normal periods, constructing a four-dimensional peak regulation index, determining a weight by using an analytic hierarchy process, and screening an optimal resource combination in each period to execute scheduling. The method can guarantee the accuracy and high efficiency of the peak regulation demand response of the power grid, and assists in improving the stability of the power system and the renewable energy consumption level.

The invention discloses a multi-scale convolution self-adaptive partial discharge fault type identification method based on characteristic parameters and moment characteristics, and relates to the field of discharge fault identification, and the method comprises the steps: obtaining a partial discharge phase three-dimensional statistical graph, and extracting a distribution relation to generate a statistical parameter graph; extracting statistical parameters based on the statistical parameter atlas, introducing preposed partial discharge occurrence judgment parameters to obtain statistical characteristic parameters, training a neural network, and constructing a statistical characteristic parameter model according to a training result; processing the statistical parameter atlas by using a multi-scale convolution technology to construct a moment characteristic model, and respectively deploying the statistical characteristic parameter model and the moment characteristic model to a partial discharge online monitoring and diagnosis platform; and obtaining a partial discharge fault type identification result based on the deployment result, analyzing the partial discharge fault type identification result by using an analytic hierarchy process, and evaluating the health state of the equipment. According to the method, the partial discharge fault type identification rate is improved, the anti-interference capability is improved, and the partial discharge type can be effectively and accurately identified.

The invention provides a tunnel health monitoring method based on distributed optical fiber sensing, and relates to the technical field of tunnel engineering health monitoring, and the method comprises the steps: carrying out the risk assessment of a tunnel through employing an analytic hierarchy process, setting a differential optical fiber laying scheme according to an assessment result, and laying distributed optical fiber sensors on the inner surface of a tunnel lining; the method comprises the following steps: acquiring original strain data through Brillouin optical time domain analysis, and preprocessing by using a moving average filtering algorithm; building a finite element model based on actual physical data of the tunnel, inverting strain data into full-field node displacement, and obtaining a complete strain tensor of a finite element unit; performing unit-level strain state evaluation, time sequence trend risk evaluation and spatial clustering risk evaluation to obtain a comprehensive risk value; and setting a dynamic evaluation threshold interval, and completing tunnel accurate region health evaluation. Accurate monitoring and risk assessment of the tunnel health state are achieved, and the method can be widely applied to the field of safety monitoring of highway and railway tunnels.

The invention belongs to the technical field of unmanned aerial vehicle power inspection, and discloses a multi-module cooperative control method for an unmanned aerial vehicle power inspection system based on a visual language model. The precise mapping of the natural language instruction and the inspection task is realized; a user does not need to depend on professional coordinate input, and target equipment and key parts can be positioned only through daily inspection verbal skills; meanwhile, a priority evaluation model and a task snapshot mechanism constructed by an analytic hierarchy process support rapid insertion and progress recovery of temporary high-priority tasks, so that the emergency troubleshooting requirement of sudden equipment exceptions can be met, orderly promotion of conventional inspection can be guaranteed, and intelligence and flexibility of substation inspection are improved; the cooperative bus built based on the time-sensitive network realizes efficient data synchronization of a plurality of modules such as a fusion model, navigation, visual acquisition and the like.

The invention relates to the technical field of underground space development, and provides a coastal bedrock type city underground space development geological suitability evaluation method comprising the following steps: analyzing key geological problems of land area and sea area underground space development, and extracting related geological factors; basic geological data are collected and classified, a geological suitability evaluation index system is constructed, and geological evaluation units are divided; subjective and objective weights are determined based on an analytic hierarchy process and an entropy weight method, and an optimal comprehensive weight is obtained through game theory combination weighting; modeling based on a grey correlation analysis method, and calculating and grading suitability scores of the evaluation units; and integrating evaluation results, and generating an underground space development geological suitability partition map of land-sea overall planning. According to the scheme, the underground space development pattern is optimized, comprehensive utilization of land and ocean resources is promoted, and safe, efficient and sustainable development and utilization of the coastal city underground space are powerfully supported.

The invention provides an urban rail transit station development intensity multi-objective optimization method in a TOD mode, and relates to the technical field of urban planning and intelligent transportation, and the method comprises the steps: analyzing the spatial relation between various types of land and urban function nodes according to the data after standardization processing, and carrying out the location value evaluation; constructing a development intensity evaluation model according to the location value evaluation, calculating the initial average plot ratio of each type of land, and deducing an initial development intensity parameter in combination with the current situation data; establishing a development intensity optimization target system according to a TOD planning principle, performing iterative optimization on the initial development intensity parameters by adopting a multi-target genetic algorithm, and outputting an optimal solution set; and carrying out comparative analysis on the optimal solution set and a current planning index, and obtaining a plot ratio index in combination with a regional development planning requirement. According to the method, a technical framework of subjective and objective collaborative optimization can be constructed by fusing GIS spatial analysis, an analytic hierarchy process and a non-dominated sorting genetic algorithm.

The invention discloses a power distribution network self-healing method for improving power supply reliability, and the method comprises the following steps: S1, collecting fault information and an operation state, constructing a fault description matrix P, and carrying out the fault positioning based on the fault description matrix P; s2, after fault positioning, judging the position of the node relative to a fault position by taking whether fault current is detected at the node as a criterion, and recording the distance x between the node and a fault branch; s3, after a fault branch and a fault node are determined, fault recovery of a non-fault area is carried out based on the distance x between the node and the fault point; s4, constructing multiple objective functions and constraint conditions, determining the weight of each objective function by adopting an analytic hierarchy process to obtain a total objective function F, and optimizing the objective functions based on an ant colony algorithm to obtain an optimal power distribution network reconstruction scheme; the power failure time can be shortened, the power supply reliability is improved, and the power grid operation reliability is improved.

The invention provides a method and a system for processing content measurement data of multi-index components in folium cortex eucommiae, and relates to the technical field of traditional Chinese medicine quality control and data analysis crossing. The method comprises the following steps: aligning standardized content data of a current batch with data of a corresponding batch in a predicted content data set; obtaining an actual detection value and predicted value pairing sequence of each index; the deviation ratio of each data pair in the actual detection value and predicted value pairing sequence of each index is calculated, and a deviation ratio analysis result is formed; and based on the deviation ratio analysis result, in combination with a pre-stored legal standard threshold and historical batch data, performing comprehensive evaluation through principal component analysis and analytic hierarchy process to obtain a multi-dimensional quality comprehensive evaluation value including specification conformity, component proportional relation and process stability. According to the method, an integrated data processing system is constructed, so that the intelligence and precision level of multi-index quality evaluation of the folium cortex eucommiae is improved.

The invention belongs to the technical field of geographic information systems and PS-InSAR, and discloses a stress-strain-considered InSAR building deformation risk assessment method, which comprises the following steps: carrying out PS-InSAR processing on time sequence SAR image data to obtain a time sequence deformation result and carrying out precision verification; adopting a PS point correction method based on a self-adaptive building contour to screen out PS points of the building; selecting five indexes of building strain, building cumulative inclination amount, building cumulative settlement amount, building age and building structure material type; building risk assessment modeling is carried out by applying an analytic hierarchy process, consistency check and weight calculation are carried out, and the maximum characteristic value of a judgment matrix established by the five risk assessment indexes is calculated; grading the indexes of the model, performing risk assessment on each index, and drawing; and verifying a building risk assessment result in combination with actual dangerous house data. According to the invention, accurate evaluation of the deformation risk level of the building is realized.

The invention discloses an enterprise operation management intelligent optimization system based on business rules, and belongs to the technical field of enterprise operation management. The system comprises core modules such as a multi-source data fusion center, a dynamic business rule engine, an intelligent optimization decision module and a closed-loop feedback unit, wherein the fusion center realizes privacy protection type multi-source data fusion by adopting federal learning; the rule engine realizes real-time adjustment of business rules without interrupting the system through rule atlas construction and incremental updating; and the optimization module is combined with an analytic hierarchy process and a Q-learning algorithm to generate a real-time optimization decision under business rule constraints. The system can improve business rule adaptation flexibility and data security, realizes decision real-time and optimization continuation, adapts to multiple industries of manufacturing, retail and logistics, and reduces enterprise operation cost and system operation threshold.

The invention discloses a coal seam group mining overlying goaf water accumulation and water inrush risk evaluation method, and relates to the field of coal mining safety. The method comprises six modules: a data acquisition module obtains basic geology, goaf and mining engineering data; the evaluation index screening module screens out key indexes such as the development height of the water-flowing fractured zone; the improved weight calculation module calculates a comprehensive weight by using an improved analytic hierarchy process-entropy weight coupling algorithm; the dynamic water flowing fractured zone prediction module combines an improved empirical formula and a mining dynamic influence coefficient to predict the height and range of a dynamic fractured zone; the risk grade evaluation module combines the weight and a fissure zone result, calculates a comprehensive index by using a fuzzy comprehensive evaluation method and divides four grades of risks; and the result output module outputs charts and reports. According to the method, the problem that a traditional method is subjective in weight and does not dynamically reflect the mining influence is solved, the evaluation accuracy and timeliness are improved, and support is provided for safe mining of a coal seam group.

The invention discloses a multi-dimensional comprehensive evaluation method for permeability resistance of overlying strata of a working face, and belongs to the technical field of mine engineering and geological safety evaluation. 12 types of core factors such as rock strength, rock core quality, physical and mechanical properties of rock mass, hydrological properties and mining influence characteristics are integrated; a full-process evaluation framework of data acquisition, index system construction, weight distribution, comprehensive modeling and verification optimization is constructed, an analytic hierarchy process and an entropy evaluation method are coupled to determine index weights, a dynamic evaluation model is constructed in combination with a fuzzy mathematics theory, and accurate classification and risk early warning of the permeability resistance of the overlying strata are realized. According to the method, through comprehensive analysis of a plurality of factors, the accuracy of overlying strata permeability resistance evaluation can be improved, so that the underground water permeation path and the permeation amount are predicted more accurately, the uncertainty is reduced, the comprehensiveness and the accuracy of evaluation are remarkably improved, and a scientific basis can be provided for mine water disaster prevention and control and safe mining.

The invention discloses an expressway operation management state comprehensive evaluation method and device based on multi-source sensing data, and the method defines six key dimensions which comprehensively describe the expressway operation health condition, including road passage, road main structure, equipment and facilities, road safety, charging operation and meteorological environment. A corresponding evaluation index is designed for each dimension based on the multi-source sensing data; and then determining each evaluation index and each dimension weight by adopting an analytic hierarchy process, and calculating each dimension score and a final comprehensive evaluation result by combining a fuzzy comprehensive evaluation method. The invention provides a multi-dimensional and explainable highway operation management state evaluation method, which can perform quantitative analysis and dynamic monitoring on the highway operation state and service level, and can be used as a basis for risk early warning and decision support to assist a management department in accurately applying measures, thereby improving the risk assessment efficiency. And the road operation efficiency, the safety level and the user travel experience are improved.

The application discloses a base station intelligent energy coordination method and system, and belongs to the technical field of energy management, and the technical solution points comprise the following steps: collecting a data set of each base station in a regional base station cluster; calculating energy constraint data based on energy data and environment data to obtain an energy scheduling sequence of each base station; obtaining a load prediction curve of each base station through a preset LSTM network model based on load data to determine a first base station; and obtaining a corresponding second base station and a third base station according to the load prediction curve of the first base station. The application obtains the load prediction curve of each base station through the preset LSTM network model and determines the first base station, obtains the second base station through the analytic hierarchy process, and obtains the third base station through multi-target reinforcement learning, so that the energy scheduling of the regional base station cluster is realized, the clean energy utilization efficiency and the energy scheduling precision are improved, and the stability of base station operation is improved.

The invention discloses a hospital energy resource intelligent management method and related equipment. The method comprises the following steps: predicting the output of renewable energy and the energy demand of each department in a future time period by using an LSTM-Attention model; on the basis of a dynamic mixed AHP analytic hierarchy process, the department energy consumption priority is evaluated by comprehensively considering the emergency state, the number of patients, the equipment operation state, historical energy consumption data and multi-dimensional factors of special medical tasks; and formulating an energy scheduling strategy through a multi-objective optimization model by combining the real-time energy consumption demand and the renewable energy source yield of the hospital according to the department energy consumption priority evaluated by the dynamic hybrid AHP method. The problems that due to insufficient application of clean energy and energy storage technology in hospitals, hospital operation cost is high, carbon emission is increased, a traditional system is difficult to dynamically adapt to complex energy consumption requirements, and stable energy supply of key areas cannot be guaranteed can be solved.

The invention discloses a pantograph-contact network system operation performance evaluation method and system. The method comprises the following steps: firstly, collecting data in real time, normalizing the collected data, and screening key hidden dangers which have power-off risks and need speed reduction operation through a two-stage risk rapid judgment mechanism; after hidden dangers are eliminated, an analytic hierarchy process is adopted to calculate index weights and initial weights of all parameters, then information entropies of all the parameters are calculated based on an improved entropy weight method to determine the dispersion degree, and real-time dynamic adjustment of the parameter weights is achieved through a combined weight method; and finally, by applying a fuzzy comprehensive evaluation method and combining the dynamically adjusted parameter weights and the membership degrees of the parameters, calculating the operation performance score of each index, then obtaining the comprehensive score of the operation performance of the pantograph-catenary system, and judging the performance grade according to the score interval. The method and the system provided by the invention are suitable for accurate evaluation of the operation performance of the icing galloping section pantograph-catenary system, and can quickly identify the operation risk and scientifically judge the performance grade.

The invention discloses a pole-mounted circuit breaker state evaluation method and system based on multi-parameter fusion, and relates to the field of data processing, and the method comprises the steps: collecting electrical, mechanical, environmental and partial discharge parameters through deploying multiple types of sensors, and extracting a feature set after abnormal value elimination, missing value interpolation and standardized preprocessing; an improved isolated forest algorithm is adopted to calculate the abnormal score of each parameter, and an improved D-S evidence theory is adopted to realize probability fusion of multi-source abnormal detection results; and based on the constructed feature layer-parameter layer-state layer three-level evaluation system, combining an analytic hierarchy process to determine an index weight, and finally outputting a comprehensive state evaluation result of the circuit breaker through fuzzy comprehensive evaluation. The method has the advantages that by synchronously collecting the electrical, mechanical, environmental and partial discharge multi-dimensional parameters of the pole-mounted circuit breaker, through improved anomaly detection and evidence fusion, in combination with a three-level index system and fuzzy evaluation, the health state of the equipment is accurately judged, the contribution degree of the parameters is determined, and a scientific basis is provided for operation and maintenance.

The invention provides a new airport site selection planning method based on bird strike risk prevention and application thereof, and the method comprises the steps: firstly screening out a pre-selected site position in a site pre-selection stage according to the limiting conditions of airport construction; comprehensively considering the degree of harm to aircrafts caused by collision of dominant bird species and bird machines in the research area, and determining the egret species, the goose and duck species and the gull species as high-risk bird species in the research area; performing high-risk bird habitat identification by using an analytic hierarchy process and a GIS analysis method; by loading, checking and visualizing weather radar data, the intensity and spatial-temporal distribution characteristics of bird activities are visually analyzed, the bird strike risk of each site scheme is evaluated, and suggestions are provided for site selection and construction of an airport. The method is suitable for airport site selection in a region where the weather radar is deployed, helps the region to do early site selection planning work, and further guarantees the flight safety.

The invention discloses an emergency communication guarantee method and system based on dynamic resource scheduling, and particularly relates to the technical field of wireless communication. According to the method, communication requirements, network states and environment interference multi-dimensional data are collected through a multi-source sensor, noise reduction and normalization preprocessing are carried out on the data, and a standardized data set is generated; fusing subjective and objective weights by adopting an analytic hierarchy process-entropy weight method, and calculating a dynamic priority value of each communication demand in combination with a service rule; then, a resource scheduling strategy library is called, channels, bandwidths and base station access resources are distributed through an improved greedy algorithm according to the priority and the resource margin, and an initial scheduling scheme is generated; and after the scheme is executed, starting full-link quality real-time monitoring, and if any one of key parameters such as bit error rate, time delay and the like is lower than a preset threshold value, triggering closed-loop dynamic adjustment: updating data, recalculating priority and calling an emergency optimization strategy to adjust resource allocation in a targeted manner until the link quality reaches the standard.

The invention relates to the technical field of compressed air energy storage and underground engineering risk control, discloses a compressed air energy storage reservoir leakage risk assessment method and system, and aims to solve the problems that an existing assessment method does not cover exploration data, is insufficient in weight determination scientificity, cannot accurately recognize geological source leakage risks and the like. The method comprises the following steps: 1) collecting investigation data and structure, operation, environment and historical leakage data; 2) constructing a risk index system containing five-level first-level indexes of investigation, structure, operation, environment and history and corresponding second-level indexes; 3) determining an index weight by adopting expert scoring and analytic hierarchy process fusion; the system comprises a data acquisition module, an index system construction module, a weight determination module, a risk assessment module and an early warning suggestion generation module, and integrated assessments are achieved.By means of the method, assessment comprehensiveness and accuracy are improved, and the method is suitable for safety management and control of the underground energy storage library.

According to the indigenous plant adaptability screening test method simulating the environmental stress condition, the transparent incubator is combined with real-time monitoring equipment such as the high-resolution miniature camera array and the optical fiber sensor, complex laboratory equipment is replaced, and the root system observation problem is solved. The environmental stress condition of a target habitat is accurately simulated, the environmental characteristics of drought, depletion, special soil structure and the like of the high and steep slope are accurately restored by adopting layered matrix and dynamic stress intervention, a systematic evaluation system is established by combining multi-index quantification and a similar analytic hierarchy process, the subjectivity of artificial experience judgment is avoided, and the evaluation accuracy of the high and steep slope is improved. And the scientificity and engineering applicability of indigenous plant screening are remarkably improved.

The invention relates to the technical field of GIS basin-type insulator performance evaluation, and discloses a GIS basin-type insulator performance evaluation method and system, and the method comprises the steps: synchronously collecting multi-physical field monitoring data through an ultrahigh frequency UHF sensor, an ultrasonic sensor array, an SF6 gas decomposition product detection unit and a thermal infrared imager; performing preprocessing and feature extraction on the monitoring data to obtain a multi-dimensional feature parameter set; performing weighted fusion calculation on the feature parameter set based on a fusion model of combined weighting of an analytic hierarchy process (AHP) and an entropy weight method, and outputting a health state evaluation index; comparing the evaluation index with a preset threshold interval to determine a performance grade and sending out an early warning; and automatically generating an evaluation report containing historical trends and maintenance suggestions. According to the GIS basin-type insulator performance evaluation method and system, multi-source information fusion and intelligent evaluation are achieved, the accuracy and reliability of state evaluation are remarkably improved, and technical guarantee is provided for safe operation of a power grid.

The invention discloses an island surrounding wave light wind resource comprehensive development suitability evaluation method and device and a medium, and relates to the field of resource development and evaluation, and the method comprises the steps: taking a suitability evaluation criterion as a criterion layer, taking an influence index as an index layer, and constructing a comprehensive development evaluation index system of a hierarchical structure; performing normalization processing on indexes in the index layer; adopting an analytic hierarchy process and a CRITIC method to determine the weight of the criterion layer based on the indexes in the index layer, and obtaining the weight; combining the two weights to obtain a combined weight of the criterion layer; and determining the suitability value of each spatial point in the peripheral area of the island based on the combination weight and the normalization result, and taking the spatial points with the suitability values higher than a set threshold value as a comprehensive development area suitable for collaborative complementation of waves, wind and photovoltaic resources. According to the method, various ocean renewable energy sources can be scientifically evaluated and reasonably optimized, and the scientificity and the accuracy of comprehensive development suitability evaluation of wave light and wind resources around an island are improved.

The invention specifically relates to an automobile fire risk dynamic assessment method and system based on multi-source data fusion, and relates to the technical field of automobile safety, and the method comprises the steps: employing an improved analytic hierarchy process to determine an index weight, building an initial assessment model based on a random forest algorithm, and outputting a 0-100 score risk value. According to the invention, road traffic and environmental meteorological data are incorporated into an evaluation system, and through verification of tens of thousands of cases, the risk identification accuracy can be effectively improved, and the missing report rate can be reduced; through a double-layer mechanism of five-minute short-term updating and daily model evolution, the risk response delay is less than 10 seconds, the problem of evaluation lag during scene switching is solved, and the method is particularly suitable for frequent switching scenes of urban expressways and suburban road sections.

The application relates to the field of intelligent path planning, and discloses an intelligent fertilizing vehicle path planning method suitable for a greenhouse environment, a road surface obstacle risk value evaluation mechanism based on an expert system and AHP (analytic hierarchy process) level analysis, road surface point cloud data established by combining binocular vision algorithm and deep learning technology, and comprehensive evaluation of road surface obstacle risks is realized. The obstacle avoidance mechanism of the traditional path planning method is effectively improved, so that the fertilizing vehicle can effectively deal with the path planning scene of a muddy path and a plant-shielded path in the greenhouse. The application improves the accessibility, timeliness and safety of the path planning of the greenhouse fertilizing vehicle.

The invention discloses a seawater cooling system state evaluation method based on a combined weight and a cloud model. The method comprises the following steps: constructing a multi-layer evaluation index system; index weights are determined by comprehensively applying various subjective and objective methods such as an analytic hierarchy process and an improved CRITIC method, and combined weighting is performed through the game theory; establishing a standard cloud model of an evaluation grade based on a 3 principle and a golden section method; actual index data are collected, an index cloud model is constructed after the actual index data are processed through an improved degradation degree formula, and an object layer and target layer comprehensive cloud model is obtained through layer-by-layer upward synthesis; and by calculating the similarity between each layer of cloud model and the standard cloud model, multi-level quantitative evaluation of the health state of the system is realized. According to the method, subjective and objective weights are fused, fuzziness and randomness in cloud model processing evaluation are combined, and scientificity and accuracy of an evaluation result are improved.

The invention relates to the technical field of live-action three-dimensional modeling, in particular to a live-action three-dimensional model quality evaluation method, which comprises the following steps of: firstly, constructing a multi-dimensional evaluation index set covering dimensions such as geometric accuracy and texture quality; an initial weight is obtained through coupling of an analytic hierarchy process and an entropy weight method, and a dynamic weight is formed by combining scene demand coefficient adjustment; then, a subjective-objective linkage relation is established through grey correlation analysis, and index scores and weights are corrected through feedback coefficients; then calculating the total quality score of a single time node; the evaluation effectiveness in the dynamic scene is verified through a time sequence consistency index; and finally outputting the comprehensive quality grade. According to the method, a multi-dimensional index set is constructed to cover full dimensions, dynamic weights are calculated in combination with scene demand coefficients, and the problems of single dimension and poor scene adaptation are solved; building subjective-objective linkage by means of grey relational degree, correcting scores and weights, and solving disjunction; and calculating a time sequence consistency index to verify dynamic coherence, solving static limitation, and adapting to full-life-cycle management and control of the model.

The invention relates to a quantitative collaborative evaluation method and system for power measurement differences and a storage medium. The method comprises the following steps: acquiring quantitative index data and qualitative index data of power measurement; performing normalization processing on the quantitative index data; respectively calculating subjective weights and objective weights of all indexes based on an analytic hierarchy process and an entropy weight method, and carrying out weighted fusion to obtain subjective and objective combined weights; processing the qualitative index data based on fuzzy comprehensive evaluation, and combining subjective and objective combination weights to obtain quantitative scores of qualitative indexes; calculating a correlation coefficient of the normalized quantitative index data and a corresponding reference sequence based on grey correlation analysis, and calculating a comprehensive correlation degree of the quantitative index; and integrating the comprehensive correlation degree of the quantitative indexes and the quantitative scores of the qualitative indexes, and calculating to obtain a comprehensive difference degree. Compared with the prior art, through subjective and objective combination and qualitative and quantitative collaborative evaluation process, accurate and consistent quantitative output of the power measurement difference is provided.