250 results about "Assessment index" patented technology

The invention discloses a risk assessment method and system based on a Bayesian network and an evidence theory, and relates to the technical field of risk intelligent assessment, and the method comprises the steps: determining an assessment dimension and an assessment index of a high-investment low-income risk of an educational institution in MOOC learning according to a human-cargo-field model and an industry report; constructing a MOOC learning risk assessment index system according to the assessment dimensions and the assessment indexes; constructing a Bayesian network structure according to the MOOC learning risk assessment index system; obtaining questionnaire data and expert opinions according to the MOOC learning risk assessment index system, and determining Bayesian network parameters based on the questionnaire data and the expert opinions; and inputting the Bayesian network parameters into the Bayesian network structure to obtain an assessment result of the high-investment low-income risk, the assessment result including a risk prediction result, a key risk factor and a sensitivity analysis result. According to the method, the high-investment and low-income risk in MOOC learning can be accurately evaluated.

The invention discloses a land value evaluation method and system based on multi-source heterogeneous data fusion, and relates to the technical field of land economic evaluation. The invention discloses a land value evaluation method and system based on multi-source heterogeneous data fusion. The method comprises four steps of multi-source data acquisition and preprocessing, standardized evaluation index quantification, index weighted fusion and value calculation, and value distribution diagram generation and output. Firstly, four types of data of background status, planning, market feedback and social perception are acquired and preprocessed; secondly, constructing a hierarchical index system to quantify indexes; determining a weight through an analytic hierarchy process and calculating a land value index according to a preset formula; and finally generating a value distribution diagram in a thermodynamic diagram form. The method realizes standardization, high efficiency and visualization of land value evaluation, can be applied to the fields of city updating, land market monitoring, government planning decision making and the like, and provides scientific support for related decision making.

The invention discloses a multi-source information fusion safety production risk intelligent early warning and disposal platform, which comprises a multi-source information acquisition module, an information preprocessing module, a multi-source information fusion module, an intelligent risk identification and early warning module, a disposal scheduling module and a data storage and interaction module, heterogeneous data such as sensor monitoring, video monitoring, equipment logs and manual reporting are collected and cleaned and standardized, and then a weighted fusion algorithm and a cross-modal deep learning model are adopted to realize multi-source data fusion; based on a preset risk assessment index system and the trained risk identification model, mapping risk levels by quantizing comprehensive risk scores, generating graded early warning information and pushing the graded early warning information in multiple channels; meanwhile, a disposal scheme is automatically matched, an instruction is issued, a closed loop is tracked, and data security is guaranteed in combination with distributed and block chain storage. Comprehensive perception, accurate identification, intelligent early warning and efficient disposal of safety production risks are achieved, and the intelligent and refined level of safety production management is remarkably improved.

The invention belongs to the technical field of traffic management evaluation, and particularly discloses and provides an urban traffic toughness quantitative evaluation method based on multi-mode traffic collaboration, and the method comprises the steps: carrying out the time-space standardization processing of multi-source data of motor vehicles, public traffic, slow traffic and external disturbance events, and generating a standardized time-space data set; based on the data set, respectively calculating a comprehensive transportation efficiency index, an alternative path redundancy index and a connection connectivity index, and constructing a toughness evaluation index set; based on the historical sequence of each index, generating a dynamic combination weight through a subjective and objective combination weighting method; and based on the index set and the dynamic weight at the current moment, calculating a comprehensive toughness index and generating a time sequence thereof to output an evaluation result. According to the method, the defects that in the prior art, an isolated analysis single mode depends on a static model are effectively overcome, and accurate multi-dimensional quantitative evaluation of the real toughness level of the complex traffic system under disturbance is achieved.

The invention provides a multi-dimensional and dynamic digital assessment system and assessment method. Comprising a support module (comprising an index knowledge base, an algorithm operation base and an evaluation model base), a multi-source index fusion center (for constructing a three-dimensional data model and integrating a multi-dimensional data resource pool), a dynamic rule configuration engine (for realizing flexible configuration through a visual interface, a model adaptation mechanism and double-track verification) and a core business module (for managing assessment indexes, evaluating indexes and evaluating indexes). And evaluating the model and plan). The support module lays a basic resource layer, a fusion center constructs a data base, a configuration engine realizes flexible verification, the business module drives full-process execution, and full-process digital management from index creation, model configuration to examination execution is realized. The problems of iteration lag, multi-scene adaptation redundancy, weak data verification and the like of a traditional system are solved, index legality is guaranteed through static grammar detection and dynamic simulation operation, data traceability is achieved through a temporary database and full-link recording, and the dynamic response capacity, scene compatibility and data reliability of the assessment system are 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 discloses a production command agent test and evaluation method, device and equipment and a medium, and belongs to the technical field of agents, and the method comprises the steps: combining any evaluation dimension in an evaluation dimension set with any test scene type in a test scene type set, and obtaining an evaluation factor combination set; performing parameter matching in an agent configuration parameter pool according to the evaluation dimension and the test scene type corresponding to the evaluation factor combination, and generating a plurality of agent configuration parameter groups corresponding to the evaluation factor combination; the production command agents corresponding to the agent configuration parameter sets are evaluated and tested, and evaluation index values corresponding to the agent configuration parameter sets are obtained; and according to the evaluation factor combination set, the agent configuration parameter group and the evaluation index value, generating total evaluation test information, and according to the total test information, testing and evaluating the to-be-evaluated production command agent. Therefore, by implementing the method, the evaluation reliability of the production command agent can be improved.

The invention relates to the technical field of employee evaluation, in particular to a high-risk industry multi-dimensional dynamic weight employee evaluation method, which comprises the following steps of: obtaining quantitative scores of three-level indexes of employees and normalizing the quantitative scores by constructing a multi-level evaluation index system; inputting the standardized score vector into a Transform-based weight learning model, dynamically learning an index weight through a self-attention mechanism, carrying out step-by-step aggregation through a multi-layer perceptron, and outputting a comprehensive score of the employee on each first-level index; inputting the comprehensive score and the historical background information into a pre-established large language model, and performing fusion analysis according to a structured template to generate a personalized evaluation text; and finally, based on the score, the text and the employee information, automatically synthesizing a visual comprehensive evaluation report containing the radar map, the information bar and the text. According to the invention, objectiveness, individuation and operability of employee evaluation are realized.

A transformer fault severity assessment method based on oil chromatographic analysis and characteristic quantification belongs to the technical field of power equipment fault diagnosis, and comprises the following steps: regularly collecting a transformer oil sample, detecting concentration data of at least one characteristic gas in oil, forming a time sequence data sequence, the method comprises the following steps: constructing a multi-dimensional input feature set as the input of an XGBoost classification model, adjusting and optimizing model parameters, training the model to output a fault type identification result, adopting k-means and SMOTE algorithms to obtain the upper bound and the lower bound of the concentration of each feature gas in a normal state and in each fault type, adopting an SHAP algorithm to calculate the Shapley value of each input feature, and obtaining the fault type identification result. And taking the absolute value of the Shapley value as the importance weight of the feature to the corresponding fault type, and carrying out weighted summation on the difference value to obtain a comprehensive evaluation index. Through the improvement of the algorithm, the fault type and severity of the transformer can be accurately evaluated.

The invention relates to the technical field of image processing, in particular to a mine safety monitoring method and system for an open-pit mining area. The method comprises the following steps: firstly, constructing different sliding windows to slide on a wedge-shaped slope image, extracting periodic characteristics of a slope surface by using similarity evaluation indexes, and comprehensively evaluating the similarity of each region of the image; secondly, determining periods of the image in vertical and horizontal directions based on similarity evaluation indexes, and optimizing block grid parameters according to the periods, so that the algorithm processing scale is matched with the periodic characteristics of the image, and the pertinence and detail representation of image enhancement are improved; and finally, the crack risk evaluation index is calculated by using the enhanced image, so that the accuracy and reliability of crack risk evaluation are remarkably improved, and the precision and robustness of slope landslide disaster monitoring are enhanced.

The invention provides a tunnel operation safety risk assessment method and system for emergencies, and the method comprises the steps: carrying out the field sampling of a specified range of a tunnel, and carrying out the analysis of the sampling data in a disaster-inducing factor index, a disaster-pregnant environment index, a disaster-bearing body index, and an emergency capability index through a safety risk assessment index system, analyzing a subjective risk weight, an objective risk weight and a comprehensive risk weight corresponding to each index of the tunnel, constructing an operation safety risk assessment cloud model of the tunnel based on a cloud theory, and deducing a subjective risk level, an objective risk level and a comprehensive risk level corresponding to each index of the tunnel. The risk coupling degree and the risk coupling coordination degree of the tunnel are analyzed according to the comprehensive risk level corresponding to each index, an operation risk report is generated and displayed, the risk evolution trend under emergencies can be pre-judged through coupling analysis, a scientific basis is provided for a tunnel operator to formulate a targeted coping strategy in advance, and the safety of the tunnel operator is improved. And loss after emergencies can be reduced.

The embodiment of the invention provides a multi-dimensional evaluation method and system for power supply toughness, and the method comprises the steps: obtaining a modeling basic data set, and constructing a power grid digital twinborn body: constructing an initial power grid digital twinborn body; coupling simulation results of electromagnetic transient simulation and electromechanical transient simulation to obtain multi-time-scale hybrid simulation data, and correcting the twin; carrying out simulation by using prefabricated disturbance scene simulation data; calculating a multi-dimensional safety evaluation index of the digital twin of the power grid according to a simulation result; determining a multi-target reward function of the agent group; performing simulation by using the intelligent agent group to obtain optimization strategy parameters of the photovoltaic inverter and the energy storage converter; parameters of the digital twin of the power grid are simulated and adjusted again; simulation output data is obtained after simulation, and a multi-dimensional evaluation result of power supply toughness is obtained through a clustering algorithm. The problems of insufficient evaluation precision, long verification period and high test risk caused by lack of a high-fidelity model in the parallel operation AC power grid are solved.

This invention discloses a method and system for constructing an investment risk assessment index system. The method includes obtaining basic data for constructing the target index system through relevant literature retrieval in a literature database; identifying investment risk factors by using a risk factor identification model to perform routine project risk factor identification on the basic data; mining risk factors for offshore photovoltaic power generation projects based on preset criteria and marine characteristic data; and determining investment risk assessment indicators based on the investment risk factors and the offshore photovoltaic power generation project risk factors. This invention can consider the characteristics of photovoltaic power generation projects and the features of the marine environment, and construct a scientific, systematic, applicable, and comprehensive investment risk assessment index system for offshore photovoltaic power generation projects according to principles.

The invention relates to a regional fire risk dynamic assessment and early warning method for an urban tunnel. The method comprises the following steps of: gridding the tunnel by taking tunnel infrastructure as a reference object; obtaining a tunnel fire accident database, and constructing a tunnel fire risk assessment index system; considering the influence of the index on the fire risk and the influence of the mobile index on spatial distribution, and determining an index weight; determining an index membership threshold, calculating an index membership degree, and obtaining a real-time initial fire risk assessment result of each region; early warning parameters are reasonably selected, the initial fire risk assessment result is corrected in combination with the single index risk, and a final regional fire risk assessment result is obtained; setting an early warning threshold value of each index under different evaluation results based on the final evaluation result of the regional fire risk occurrence probability; and comparing the index early warning value according to the index data measured by the risk sensing equipment, and outputting a single-index fire risk early warning result to realize single-index fire risk early warning. The method is high in pertinence, high in accuracy and high in sensitivity.

The invention relates to the technical field of information security, in particular to a penetration test effect evaluation method and system based on an attack mode framework, and the method comprises the steps: firstly, constructing an evaluation model comprising a target layer, a criterion layer and an index layer; the evaluation indexes under each criterion are weighted through a large language model, and the indexes are quantitatively scored by experts. And for each criterion, on the basis of a grey theory, calculating a comprehensive evaluation vector of the criterion by using index scores, weights, a preset comment set and a whitening weight function so as to obtain a quantitative score and a qualitative evaluation result. And finally, calculating a final comprehensive evaluation result of the target layer by integrating the quantitative score vectors and the criterion weights of all the criteria. During decision making, the final result needs to be combined with the qualitative evaluation conclusion of each criterion so as to formulate a comprehensive and targeted security reinforcement strategy. According to the invention, the accuracy of penetration test effect evaluation is improved.

The invention discloses a multi-process background field comprehensive evaluation method and a related device. The method comprises the following steps: constructing a multi-process characterization element set facing a power weather forecast demand; inputting the multi-process characterization elements in the multi-process characterization element set into a comprehensive evaluation model based on evaluation index classification and different standardization technologies to obtain each background field index value after evaluation; performing nonlinear score assignment on each evaluated background field index value by adopting a Gaussian attenuation method, and endowing each evaluated background field index value of each process in each background field with a weight coefficient; and calculating a comprehensive score of each background field according to the non-linear score assignment result of each background field index value after evaluation and a weight coefficient assigned by each background field index value after evaluation of each process in each background field, and evaluating each background field according to the comprehensive score of each background field. According to the method and the related device, the systematicness deviation between the background field screened by the method and the electric power weather forecast demand is relatively low.

This invention proposes a method for assessing the resilience of heavy platforms based on the DA-PSR model and complex networks. Taking heavy platforms as the object, an objective resilience assessment system is constructed. An assessment index system with causal relationships is established, and a screening method for the assessment index system based on node betweenness values ​​in complex network theory and the k-means algorithm is proposed. This results in a simplified assessment index system where the remaining node betweenness values ​​account for 52.99% of the total betweenness values ​​and the remaining cluster center values ​​account for 90.55% of the total cluster center values. An index weighting method based on mutual information theory and an index calculation method based on extreme damage quantification are proposed. The PSR framework theory is improved through dimensional analysis, and a resilience DA-PSR assessment model is constructed. Considering the performance requirements driven by tasks, a criterion quantification and dynamic grading method based on task requirements is proposed. The assessment shows that a heavy platform with a resilience assessment value of 0.7373 exhibits different assessment levels of "excellent," "medium," and "poor" under different tasks.

The invention discloses a power grid safety production risk early warning method based on big data mining, and relates to the technical field of power grid management. Through a big data mining technology, data is obtained from multiple core dimensions, an evaluation index set containing 36 items of data is constructed, the index coverage degree is high, correlation analysis is performed based on index data, and the early warning efficiency is high. The method combines subjective and objective combination weighting, combines subjective weight and objective weight and performs fusion analysis, avoids subjective randomness of single dependence on expert judgment and limitation that pure data driving may deviate from business logic, obtains a more accurate power grid safety production risk assessment index, and performs dynamic early warning on power grid safety production. And the efficiency and reliability of power grid safety management are improved.

The invention discloses a low-carbon oriented control detailed planning scheme evaluation method and device. The method comprises the following steps: constructing an evaluation index system; wherein the evaluation index system comprises a plurality of evaluation indexes corresponding to different index attributes; dynamically screening the evaluation indexes to obtain index subsets corresponding to different scheme types; identifying a scheme type of a to-be-assessed scheme, determining to-be-assessed indexes of the to-be-assessed scheme according to the index subset corresponding to the scheme type of the to-be-assessed scheme, and determining a standard value corresponding to each to-be-assessed index according to the scheme type of the to-be-assessed scheme; and collecting an actual value of each to-be-evaluated index, and determining an evaluation result of the to-be-evaluated scheme according to the index attribute of each to-be-evaluated index, the actual value of each to-be-evaluated index and the corresponding standard value. According to the invention, the evaluation accuracy and reliability of the control detailed planning scheme can be improved.

The invention provides an urban power distribution network multi-demand side resource adjustment capability evaluation and optimization method, and relates to the field of power systems and automation thereof. The method comprises the following steps: S1, collecting data of various demand side resources, and constructing a multi-demand side resource pool; s2, establishing a multi-dimensional evaluation index system for the multi-demand side resource pool; s3, determining the comprehensive weight of each evaluation index in the multi-dimensional evaluation index system by adopting a combined weighting method; s4, based on the comprehensive weight, calculating comprehensive adjustment capability evaluation values of various demand side resources by adopting a TOPSIS method; and S5, according to the comprehensive regulation capability evaluation value and the real-time safety state of the power distribution network, constructing a resource optimization calling model, and generating an optimization calling strategy set. According to the urban power distribution network multi-demand side resource adjustment capability evaluation and optimization method, the management and control capability and the safe operation level of the power distribution network on the multi-demand side resources are improved.

The invention discloses a WSRS framework-based ecological safety assessment method for a drainage basin in an arid region, relates to the technical field of ecological assessment, and solves the technical problems that the prior art is not adaptive to a coupling process of water, salt, evapotranspiration and underground water and lacks key factors, and an assessment method lacks weight uncertainty description and robustness analysis. The method comprises the steps of S1, acquiring multi-source data of a target drainage basin, and performing data preprocessing; s2, constructing a WSRS evaluation index system, and carrying out standardization processing on indexes; s3, based on the standardized indexes, determining the comprehensive weight of each index by adopting a subjective and objective combination weighting method; s4, performing comprehensive evaluation based on the comprehensive weight, and quantifying uncertainty of an evaluation result by adopting a cloud model to obtain an ecological safety index; s5, constructing a composite stress model and correcting an ecological safety index; and S6, carrying out risk grade division and result visualization. The method has the advantages that the arid region process adaptability is high, the evaluation result is stable and explainable, and the like.

The invention discloses a data asset compliance evaluation method, equipment and a medium, and relates to the technical field of data asset compliance evaluation. The method comprises the following steps: acquiring enterprise data assets, and evaluating the enterprise data assets based on a preset evaluation rule to obtain an evaluation index; based on the evaluation index, determining an influence factor corresponding to the evaluation index, and allocating a weight coefficient for the influence factor; weighted summation is carried out on the influence factors and the weight coefficients corresponding to the influence factors, and evaluation index scores are calculated; and generating compliance risk assessment results and repair suggestions of the enterprise data assets based on the assessment index scores. According to the method, the same measurement standard is established for the enterprise data assets through the unified evaluation rule and influence factor, and the evaluation index score is calculated through weighted summation, so that objective evaluation of the compliance of the data assets is realized.

This invention relates to a multi-dimensional dynamic assessment method and system for waterway operation status, belonging to the field of waterway transportation operation monitoring technology. This invention fuses processed data at the data layer, feature layer, and decision layer to form a deep coupling of multi-modal data; constructs a multi-dimensional waterway operation status assessment index system; utilizes this index system for real-time dynamic assessment of multi-dimensional waterway operation status; trains a deep learning model using historical multi-modal time-series data; and uses the deep learning model for time-series prediction and graded early warning of waterway operation status. Based on the assessment and early warning results, it outputs executable decision-making schemes. This invention constructs an integrated assessment system encompassing navigation environment, vessel flow, waterway siltation, structural health, hydrometeorology, and navigation safety dimensions, achieving a comprehensive depiction of waterway operation status. It employs a three-level fusion strategy to break down data silos from multiple sources, improving the accuracy and reliability of status assessment.

The invention provides a multi-modal data-based driver post suitability evaluation method, an edge computing device and a medium. The method comprises the steps of obtaining behavior data, physiological data and vehicle driving data of a driver in a simulated driving environment; on the basis of the behavior data, the physiological data and the vehicle driving data, post suitability evaluation indexes of the driver are calculated, and the post suitability evaluation indexes at least comprise a safety index, an attention stability index and a physiological anti-fatigue ability index; and determining the post suitability level of the driver based on the post suitability evaluation index. The method can reduce the evaluation cost of the driver post suitability and improve the accuracy of the evaluation result.

The invention discloses a dynamic evaluation method, system and equipment for integrity of a wetland ecosystem and a medium, and particularly relates to the technical field of ecosystem evaluation, and the technical key points are as follows: constructing an integrity evaluation hierarchical structure model of the wetland ecosystem; wherein the wetland ecosystem integrity evaluation hierarchical structure model comprises a target layer, an element layer and an index layer; the target layer is a wetland ecosystem integrity evaluation target; the element layer comprises ecological system integrity evaluation elements related to the dynamic change of the water level; the index layer comprises evaluation indexes used for quantifying the ecological system integrity evaluation elements; obtaining current situation data of each evaluation index of the index layer under different water level scenes, and calculating a standardized quantized value of each evaluation index based on the current situation data; and determining the weight of each evaluation index, and calculating the wetland ecosystem integrity comprehensive index of the target layer based on the standardized quantized value and the weight of each evaluation index.

The invention provides a method for constructing a data quality evaluation model, and belongs to the technical field of quality evaluation, and the method comprises the steps: collecting a to-be-evaluated data set, and obtaining a business demand and an application scene of the to-be-evaluated data set; determining an assessment index vector of the to-be-assessed data set based on the business demand and the application scene of the to-be-assessed data set; based on the to-be-evaluated data set and the evaluation index vector, determining a training quality feature matrix and a test quality feature matrix; and constructing a quality evaluation model based on the training set and the training quality feature matrix, and evaluating and optimizing quality evaluation performance based on the evaluation index vector, the test set and the test quality feature matrix. The method can enhance the capturing capability of the model for the data quality characteristics, achieves the high-precision evaluation of dynamic weighting, improves the intelligence and stability of the quality evaluation model, and improves the adaptability of the model in the quality management and analysis scenes of complex data.

The invention discloses a distribution line lightning stroke risk assessment method, device and equipment and a medium, and belongs to the technical field of power equipment risk assessment, and the method comprises the steps: obtaining the lightning stroke risk assessment index data of each line segment on a target distribution line after preprocessing, constructing a forward matrix, carrying out the standardization processing of the forward matrix, and obtaining the lightning stroke risk assessment index data of each line segment on the target distribution line; obtaining a standardized matrix of lightning stroke risk assessment indexes; based on this, determining the weight of each lightning stroke risk assessment index by using an entropy weight method; constructing a weighted standardized matrix based on the weight and the standardized matrix; and based on the weighted standardization matrix, a TOPSIS method is adopted to determine a lightning stroke risk assessment result of each line section on the target distribution line. The method is effective and accurate, and accurate identification and quantitative sorting of lightning stroke risks of the distribution line section can be realized.

This invention provides a dynamic management method and system for multi-level assessment indicators of the resilience of nearshore bridges throughout their entire life cycle, relating to the field of structural resilience assessment and management technology. The method includes: acquiring multi-source heterogeneous maintenance data streams throughout the entire life cycle of the nearshore bridge; processing these data streams through time-series alignment and feature dimensionality reduction mapping to obtain a basic feature matrix of the bridge's service status; and performing conditional routing and data stream processing based on this basic feature matrix to obtain corrosion evolution calculation potential field distribution data, structural dynamic stiffness attenuation tensor, and structural life-cycle degradation confidence distribution vector. This invention accurately obtains resilience indices that truly reflect the bridge's resistance to degradation through multi-step quantification calculations, clarifies the sensitivity differences of assessment nodes, formulates differentiated dynamic maintenance strategies, and constructs a closed-loop management system throughout the entire process, thereby achieving intelligent bridge maintenance, improving maintenance efficiency, and reducing costs.

This invention relates to the field of construction monitoring technology, specifically to a method and system for monitoring structural offsets using BIM technology. The method involves using a multi-source sensor cluster to collect real-time location information of multiple components within the construction structure, obtaining real-time monitoring data. Based on the real-time monitoring data and the preset coordinates of the components in the BIM model, a first offset evaluation index for the target component is calculated. The component importance is then obtained. The first offset evaluation index is corrected based on the component importance score to obtain a second offset evaluation index. This second offset evaluation index is compared with a preset offset threshold to determine monitoring and early warning information. This approach enables dynamic assessment of offset risks, establishes an early identification mechanism for potential problems, and optimizes the early warning system. It can dynamically capture offset trends and comprehensively consider them, achieving early risk identification and optimized early warning, thereby improving the accuracy and efficiency of construction structures.

The invention relates to the technical field of performance evaluation, and discloses a dynamic weight-based performance analysis processing method and device, equipment and a medium. The method comprises the steps of obtaining a dynamic weight corresponding to an air route feature through a dynamic weight model based on the air route feature; identifying a label of the target object, and determining an evaluation index of the target object; calculating a comprehensive index completion rate according to the dynamic weight; and generating a corresponding processing strategy based on a preset rule, the comprehensive index completion rate and the evaluation index. According to the method and the device, the technical problems of insufficient evaluation accuracy, low evaluation matching efficiency and evaluation linkage lagging caused by index solidification in the process of evaluating the post efficiency in the prior art are solved.