73 results about "Fuzzy relation matrix" patented technology

The invention discloses a slope ecological restoration suitability evaluation method, medium and equipment, and relates to the technical field of slope ecological restoration, and the method comprises the steps: obtaining slope ecological restoration data, and obtaining a slope ecological restoration suitability evaluation index according to the data; calculating the weight of the evaluation index by adopting a fuzzy analytic hierarchy process based on the evaluation index; scoring each evaluation object according to the evaluation indexes, and establishing a fuzzy relation matrix; and according to the fuzzy relation matrix and the weight vector, obtaining a comprehensive suitability evaluation score of each evaluation object, and judging a suitability grade of slope ecological restoration. According to the method, the ecological restoration suitability of the arid and semi-arid land high and steep rock slope can be quantitatively evaluated.

The invention discloses a regulation and control quota distribution method and system fusing subjective and objective multi-dimensional features. The method comprises the following steps: acquiring electrical load data, historical response behavior data and subjective response intention information of a user; firstly, a Ward system is used for clustering, users are clustered according to active power, then a primary clustering center is used as an initial clustering center of secondary clustering, FCM clustering is carried out, and a typical load curve of the users is described based on a secondary clustering method; load prediction is carried out based on an NARX neural network, a predicted load curve is compared with a typical load curve, and adjustable potential is calculated; constructing a DR feature data set; and the DR feature data set is fused with an entropy weight method and an analytic hierarchy process to obtain a combined weight, a fuzzy relation matrix is constructed, a user comprehensive score is quantified, and a comprehensive response potential score of the user is formed.

The invention discloses a fishery sea fishing resource assessment method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining multi-dimensional data information of a to-be-assessed target sea area; determining a plurality of evaluation factors in the data information of each dimension; constructing a hierarchical structure model of fishery and sea fishing resource evaluation based on the multi-dimensional data information and the corresponding evaluation factors; based on the hierarchical structure model, determining the data information of each dimension and the index weight of the corresponding evaluation factor through an analytic hierarchy process; constructing a fuzzy relation matrix through fuzzy mapping representation based on the evaluation factor in combination with a preset comment set; performing fuzzy synthesis operation according to the index weight and the fuzzy relation matrix to obtain a fuzzy comprehensive evaluation result; and determining a final evaluation result of the target sea area based on the fuzzy comprehensive evaluation result. The method can accurately realize fishery sea fishing resource evaluation, and can be widely applied to the technical field of fishery resource evaluation.

The invention discloses an intelligent decision-making method and system based on deep learning, and relates to the field of data processing. The method comprises the steps of obtaining place data and corresponding attribute data of a to-be-decided project; establishing a fuzzy relation matrix between the places and the attributes; generating a network model reflecting trust relationship strength among users through trust propagation operation of the graph neural network; identifying a community structure containing a community overlapping degree through a community discovery algorithm; and according to the trust relationship strength between the users and the community overlapping degree, calculating an influence weight of a decision maker, forming a group consensus through a robust optimization method, and generating a decision result of the project to be decided. Aiming at low network relation modeling precision caused by multi-source heterogeneous data in bus station layout decision making in the prior art, the method and the device have the advantages that the network relation modeling precision is low through accurate modeling of an information propagation path in a complex trusted network, effective dimension reduction representation of a high-dimensional feature space and robust optimization solution in an uncertain environment; therefore, the calculation precision and robustness of the bus station layout intelligent decision-making system are improved.

The invention discloses an auxiliary medical diagnosis method based on a kernel fuzzy rough set, and belongs to the technical field of medical data analysis, and the method comprises the following steps: S1, carrying out the standardization processing of medical data, and obtaining the data after the standardization processing; s2, calculating a kernel fuzzy relation matrix by using a Gaussian kernel function according to the normalized data; s3, selecting an attribute subset according to the kernel fuzzy relation matrix, and constructing a multi-granularity fuzzy information particle set; s4, calculating fuzzy approximation precision according to the multi-granularity fuzzy information particle set; s5, calculating the particle anomaly degree of the fuzzy information according to the fuzzy approximation precision; s6, calculating anomaly scores of all samples according to the fuzzy information particle anomaly degree; s7, judging whether the abnormal scores of the samples are greater than a threshold value one by one, if so, outputting medical data abnormal points, and assisting a doctor in diagnosis; otherwise, the data are regarded as normal data until all samples are judged. According to the method, the problems of extraction and fusion of multi-granularity data features of existing medical data anomaly detection are solved, nonlinear medical data with fuzzy uncertainty can be effectively processed, and therefore doctors can be assisted in finding the condition of a patient more quickly and more accurately.

The invention relates to a science and technology project evaluation method and system, and relates to the technical field of multi-index decision and intelligent modeling. Comprising the steps of collecting multi-dimensional data of finance, intellectual property, teams, historical projects and the like of science and technology projects; constructing an evaluation index system; constructing a cognitive map by taking the indexes as nodes and combining statistical correlation and expert rules; a graph attention network (GAT) is utilized to train the graph, and structural causal weights among indexes are extracted; fusing the structure weight and the original fuzzy relation matrix to form a structure enhanced fuzzy relation matrix; and in combination with a weight vector determined by a fuzzy analytic hierarchy process (FAHP), performing fuzzy weighted comprehensive evaluation, and outputting a project grade and an interpretable result. According to the method, the accuracy, self-adaptability and interpretability of science and technology project evaluation are effectively improved, and the method is suitable for complex project evaluation tasks in a multi-source heterogeneous data environment.

The invention discloses a production area rice quality evaluation method based on multi-dimensional index fusion, and the method comprises the steps: determining a subjective weight through employing an analytic hierarchy process, calculating an objective weight through combining with a CRITIC method, and obtaining a comprehensive weight through multiplication integration normalization; establishing an index grading standard based on a sample data quantile, calculating the membership degree of each index by using a reduced half trapezoidal distribution function, and constructing a fuzzy relation matrix; and finally, synthesizing the comprehensive weight and the fuzzy relation matrix, and judging the rice quality grade according to a maximum membership degree principle. Compared with an existing evaluation criterion, the evaluation method comprehensively considers the subjective weight and the objective weight of each index, the rice quality can be evaluated more accurately, and therefore the rice grade is scientifically judged.

The invention provides a shipyard power distribution network health degree assessment method and system, and relates to the technical field of health state assessment and management of power systems. The method comprises the following steps: constructing a shipyard power distribution network health degree evaluation system by adopting an analytic hierarchy process, performing grading and scoring according to corresponding national standards, and determining subjective weights of indexes; calculating objective weights of the indexes by adopting an entropy weight method; calculating a comprehensive weight based on the subjective weight and the objective weight; and based on the comprehensive weight and the fuzzy relation matrix, performing shipyard power distribution network health degree evaluation by adopting a double-layer judgment criterion. Quantitative evaluation and hierarchical management of the health degree of the shipyard power distribution network are realized, a double-layer judgment criterion is introduced in evaluation grade judgment, the accuracy and rationality of an evaluation result are ensured, the stability of the power distribution network can be effectively improved, the unplanned shutdown risk is reduced, the power resource configuration is optimized, and the production safety and the product quality are guaranteed.

The invention belongs to the technical field of prediction control, and discloses a temperature prediction method and system based on a particle swarm algorithm and a matrix semi-tensor product, and the method comprises the steps: collecting data, screening the collected data, and determining key influence factors of greenhouse temperature changes; defining a fuzzy set, performing discourse domain division on each key influence factor, fuzzifying data in each discourse domain to obtain a membership function of each discourse domain, and vectorizing the membership function of each discourse domain; establishing a fuzzy rule and a fuzzy relation matrix, and obtaining a plurality of predicted temperatures by using the fuzzy rule and the fuzzy relation matrix based on the membership function vector of each discourse domain of the key influence factor; and processing the plurality of obtained prediction values by using a time-based weighting algorithm to obtain a final prediction result. According to the invention, an accurate prediction and optimization strategy is provided for temperature regulation, real-time optimization regulation of the greenhouse temperature is realized, energy consumption is reduced, the crop yield is improved, and agricultural intelligence is promoted.

The invention relates to load prediction, in particular to a power grid load prediction method, which comprises the following steps of: decomposing a power grid load prediction problem into different levels, constructing a judgment matrix, and calculating a preliminary weight of each factor based on the judgment matrix; calculating a variation coefficient of each factor, and adjusting the initial weight of each factor by using the variation coefficient to obtain a weight coefficient of each factor; constructing a grey incidence matrix of each factor according to the historical data of the power grid load, and calculating the correlation degree between each factor and the power grid load based on the grey incidence matrix of each factor; combining the weight coefficient and the correlation degree of each factor to construct a fuzzy relation matrix of each factor, and obtaining an electric quantity prediction matrix based on the fuzzy relation matrix of each factor; inputting the electric quantity prediction matrix into a pre-trained power grid load prediction model to obtain a first power grid load prediction result; according to the technical scheme provided by the invention, the defect that the power grid load is difficult to accurately predict in the prior art can be effectively overcome.

The invention provides a storage battery automatic bridging method and device based on battery data detection, and the method comprises the following steps: obtaining the battery position information of each storage battery unit in a storage battery pack, and collecting the battery parameters of each storage battery unit; preprocessing battery parameters, and extracting static parameters and dynamic parameters; constructing a characteristic fuzzy relation matrix based on the battery characteristic parameters, and performing fuzzy comprehensive evaluation on the storage battery unit according to the characteristic fuzzy relation matrix; inputting the abnormal battery characteristic parameters of the abnormal storage battery units into a preset storage battery fault identification model, and identifying fault storage battery units in the abnormal storage battery units; and if the storage battery fault identification model identifies the faulty storage battery unit, generating an automatic bridging task of the automatic bridging device, and controlling the automatic bridging device to realize automatic bridging processing on the faulty storage battery unit through the automatic bridging task. According to the invention, the fault storage battery can be automatically detected and bridged, and the efficiency is high.

The invention provides a soft rock damming safety evaluation method and system based on fuzzy analytic hierarchy process, and belongs to the technical field of water conservancy and hydropower engineering safety evaluation, and the method comprises the steps: constructing a target layer-criterion layer-index layer three-level evaluation model framework; determining indexes in the index layer according to the evaluation items of the item layer; calculating the weight of each index by adopting an analytic hierarchy process; establishing a fuzzy relation matrix; performing synthesis operation on the weight of each index and the fuzzy relation matrix by using a fuzzy synthesis operator to obtain an evaluation vector; and judging the safety level of damming according to the evaluation vector. According to the method, the confidence interval based on credibility distribution is constructed, a traditional single evaluation result is replaced, uncertainty in the evaluation process is fully reflected, a more comprehensive and scientific information basis is provided for decision makers, and therefore the decision makers are assisted to make more reasonable and reliable engineering decisions.

The invention provides a coal mine water disaster water inrush early warning grading method, and relates to the technical field of coal mine safety engineering and intelligent monitoring, and the method comprises the steps: collecting the multi-source basic data of a coal mine area in real time; constructing a first-level index-second-level index layered influence factor set based on a water source condition, a water guide channel and a dynamic factor of coal mine water disaster water inrush, and introducing an index dynamic correlation coefficient; defining an early warning grade-symbol-judgment standard-emergency response four-dimensional judgment set of the coal mine water disaster; respectively calculating the membership degree for the measured value of each secondary index in the multi-source basic data, and constructing a fuzzy relation matrix; dynamically calculating the real-time weight of each level of index according to the mining process and the index dynamic correlation coefficient; and based on the real-time weight and the fuzzy relation matrix, calculating and obtaining a corresponding early warning grade and an emergency response in the four-dimensional evaluation set. According to the method, full-period water inrush risk grading early warning of bottom plate limestone water, top plate sandstone water, goaf water and composite water disasters under complex geological conditions can be achieved.

The present invention relates to load forecasting, and in particular to a power grid load forecasting method, which decomposes a power grid load forecasting problem into different levels, constructs a judgment matrix, and calculates the preliminary weight of each factor based on the judgment matrix; calculates the coefficient of variation of each factor, and uses the coefficient of variation to adjust the preliminary weight of each factor to obtain the weight coefficient of each factor; constructs a grey correlation matrix of each factor according to historical power grid load data, and calculates the correlation between each factor and the power grid load based on the grey correlation matrix of each factor; constructs a fuzzy relationship matrix of each factor based on the weight coefficient and correlation of each factor, and obtains an electric quantity prediction matrix based on the fuzzy relationship matrix of each factor; inputs the electric quantity prediction matrix into a pre-trained power grid load forecasting model to obtain a first power grid load forecasting result; the technical solution provided by the present invention can effectively overcome the defect of the prior art that it is difficult to accurately predict the power grid load.

The invention discloses an orthodontic auxiliary decision-making method based on fuzzy comprehensive evaluation and an operation system thereof, which are used for providing a personalized orthodontic treatment scheme, and specifically comprise the following steps: firstly, comprehensively analyzing key factors influencing an orthodontic treatment effect, screening out representative evaluation indexes, and determining the evaluation indexes; an evaluation system of orthodontic treatment decisions is constructed; then, respectively calculating a subjective weight and an objective weight by adopting an analytic hierarchy process and an entropy weight method, and optimizing weight distribution in combination with a game theory to obtain a comprehensive weight of each index; and finally, based on a fuzzy comprehensive evaluation method, constructing a trapezoidal membership function, establishing a fuzzy relation matrix, and determining an optimal treatment scheme through a maximum membership principle. Scientific and accurate auxiliary decision support can be provided for orthodontic doctors, the individuation level of a treatment scheme is effectively improved, and the developed operation system application can improve the diagnosis efficiency of young doctors.

The invention discloses a method and a system for analyzing an enterprise production state based on an electric power index, and relates to the field of electric power indexes. The method comprises the following steps: constructing an evaluation index system comprising two first-level indexes, namely production state data and export trade state data; an autoregressive moving average model and a Kendall rank correlation coefficient algorithm are used to construct a prediction model of the power consumption index to the export amount index; the enterprise production state is analyzed based on a panel space model, and an enterprise production state early warning index is obtained; setting a weight Wi of each evaluation index according to the enterprise production state early warning index, and constructing a fuzzy relation matrix R according to the evaluation index system and the weight Wi of each evaluation index; constructing a fuzzy evaluation matrix B according to the weight Wi and the matrix R; according to the matrix B, the maximum membership degree principle is adopted to calculate the production state and export trade state evaluation grade of the target enterprise; aiming at low analysis precision caused by neglecting correlation among indexes in foreign trade enterprise analysis in the prior art, the analysis precision is improved.

The invention discloses a fire-fighting reconnaissance robot system hardware reliability evaluation method, which comprises the steps of collecting hardware performance data and key environment stress data of a fire-fighting reconnaissance robot, and constructing basic evaluation data; extracting a core evaluation factor evolved along with the change of the fire scene condition, and determining reliability index data according to the core evaluation factor; determining a subjective weight and an objective weight according to the real-time reliability index data in the current environment; performing dynamic adjustment on the subjective weight and the objective weight of the fire-fighting reconnaissance robot index to obtain a self-adaptive comprehensive weight vector; and constructing a fuzzy relation matrix by using the core evaluation factor and the comprehensive weight vector, and performing synthesis operation to obtain a real-time updated system reliability level. According to the reliability evaluation method, real-time, dynamic and accurate evaluation of the reliability of the fire-fighting reconnaissance robot hardware can be realized, and intelligent decision support is provided for dynamic task decision and imminent maintenance of the robot.

The invention relates to the technical field of computer science and technology, and discloses a karst metal underground mine hidden disaster-caused water disaster risk evaluation method comprising the following steps: constructing a three-level evaluation index system of a karst metal underground mine comprising a target layer, a criterion layer and an index layer; analyzing the expert analysis risk level of the second-level index; correcting expert analysis risk levels to obtain membership degrees of the second-level indexes relative to different risk levels so as to construct a fuzzy relation matrix of the karst metal underground mine; calculating a first-level index weight of a first-level index corresponding to the criterion layer and a second-level index weight of a second-level index corresponding to the criterion layer, and performing fuzzy synthesis operation on the fuzzy relation matrix and the second-level index weight to obtain a first index risk probability of the first-level index; and performing fuzzy synthesis operation on the first index risk probability and the first-level index weight to obtain a comprehensive risk level corresponding to the target layer. According to the invention, the monitoring accuracy of major safety accidents caused by hidden water disasters can be improved.

The invention discloses a resource allocation method and device, a computer program product and electronic equipment. The method comprises the following steps: acquiring project information of a target project; multiple evaluation indexes of the target project are determined according to the project information, index weights of the evaluation indexes are determined based on an index judgment matrix, and matrix elements of the index judgment matrix are used for reflecting the importance proportion between every two evaluation indexes; the feasibility level of the target project is determined based on a fuzzy relation matrix and the index weight of each evaluation index, and matrix elements of the fuzzy relation matrix are used for representing the membership degree of each evaluation index to comments of different levels; and determining a cloud resource allocation strategy of the target project according to the project information and the feasibility level, and allocating corresponding cloud resources to the target project according to the cloud resource allocation strategy. The technical problems of unreasonable resource allocation and untimely risk response existing in a cloud resource scheduling strategy for formulating a project based on static information are solved.

The invention belongs to the technical field of cloud computing networks, and discloses a computing power network workload spatio-temporal dynamic prediction method and device, equipment and a medium, and the method comprises the steps: determining a fuzzy set for identifying a workload mode through employing a clustering algorithm based on dynamic time warping according to a performance index during operation; determining a state transition conditional probability matrix of the computing power node, the heterogeneous hypergraph and the working load mode; adopting hypergraph convolution kernel learning to obtain a heterogeneous feature fusion model of workload and computing power nodes; processing the fuzzy set by adopting a fuzzy membership covariance, and further training by adopting a time convolution network of a dynamic receptive field to obtain a time sequence feature of a workload; and according to the heterogeneous feature fusion model and the time sequence features of the workload, carrying out space-time fusion training of cross entropy measurement probability and fuzzy uncertainty by adopting a probability intuitionistic fuzzy relation matrix to obtain a workload space-time dynamic prediction model. The method has the beneficial effect that the error rate of resource scheduling decision is reduced.

The invention discloses a living environment human factor engineering optimization method and system based on AHP-fuzzy comprehensive evaluation. The method comprises the steps that physical parameters (including illumination intensity distribution, air particulate matter concentration gradient, sound pressure level spectrum data and space geometric topology information) of a living environment are collected in real time through a multi-source sensor network; constructing a hierarchical structure of the evaluation model by using an analytic hierarchy process and calculating a weight vector; and constructing a membership function and a fuzzy relation matrix by combining a fuzzy comprehensive evaluation method, and generating an optimization scheme of cabin layout and facility configuration through a multi-dimensional constraint optimization model. By integrating AHP and fuzzy comprehensive evaluation and introducing a real-time data dynamic adjustment mechanism, the accuracy and practicability of living environment evaluation and optimization are remarkably improved. The method can be widely applied to the fields of smart home, cabin design, human settlement environment engineering and the like.

The invention relates to the technical field of under-mine disaster risk assessment, in particular to an under-mine sensor disaster risk assessment method based on four-dimensional information diffusion, which comprises the steps of obtaining step data according to historical reference data, arranging a sensor in a space structure according to the step data, and constructing a space monitoring field, acquiring sensor position data and disaster data; according to the method, a sensor disaster risk is defined as a fuzzy risk, then disaster information of all sensors affected by disasters is diffused to a whole space monitoring field constructed based on a disaster scene based on four-dimensional information diffusion, an obtained information matrix is processed into a fuzzy relation matrix, and then a sensor disaster risk curved surface is constructed. Therefore, the sensor disaster risks of all the sensors in the disaster scene are described. According to the invention, through identification and diffusion of the sensor disaster data in the space monitoring field, assessment and early warning are accurately carried out on the disaster risk under the mine.

The invention belongs to the technical field of rockburst prediction of laneway engineering, and particularly discloses a multi-parameter rockburst prediction method based on analytic hierarchy process and fuzzy mathematics, which takes lithologic conditions, stress conditions and surrounding rock conditions as evaluation indexes to form rockburst grading judgment criteria of 13 evaluation indexes, is beneficial to solving the problem of single selection of rockburst indexes, and improves the rockburst prediction accuracy. The rock burst prediction accuracy is improved; meanwhile, a comprehensive evaluation model is constructed by combining analytic hierarchy process and fuzzy mathematics and comprises a fuzzy mathematical model and a hierarchical structure model which are synchronously carried out, a fuzzy relation matrix is obtained through the fuzzy mathematical model, the weight of each evaluation index is obtained through the hierarchical structure model, and then output of the two models is fused to obtain a rock burst comprehensive prediction result. And by quantitatively analyzing the evaluation indexes, the subjectivity of expert experience is reduced, so that the prediction result is more stable and reliable.

The invention relates to the technical field of navigation safety management, and discloses a coastal water area navigation safety early warning method and system based on grids, and the method comprises the steps: constructing an evaluation factor set, and obtaining the real-time parameters of each evaluation factor in each grid unit; calculating a membership degree set of each evaluation factor of each grid unit through a membership degree function, and constructing a fuzzy relation matrix of each grid unit; constructing a judgment matrix according to preset scale values among the evaluation factors, and obtaining weight vectors of the evaluation factors according to the judgment matrix; generating a fuzzy evaluation result according to the fuzzy relation matrix and the weight vector; and obtaining a comprehensive safety risk value of each grid unit according to the fuzzy evaluation result and a preset risk level weight, and further obtaining a risk level of each grid unit. According to the scheme, a scientific decision basis can be provided for navigation safety management, emphasized water areas can be defined, supervision measures can be optimized, a safety risk assessment tool can be provided for ship navigation, and the safety management level can be improved.

The present invention discloses a method, device, equipment and medium for determining the risk level of a power grid situation. The method comprises: obtaining a power grid situation data set of a power grid to be tested; generating a fuzzy relationship matrix corresponding to the power grid situation data set based on similarity factors between two power grid situation data, and calculating a transitive closure matrix corresponding to the fuzzy relationship matrix; inputting each column of the transitive closure matrix into a pre-trained situation awareness model to obtain risk level description data corresponding to each power grid situation data; and determining the power grid situation risk level corresponding to each power grid situation data based on the risk level description data. The present invention solves the problem of difficulty in predicting power grid situation and determining power grid situation risk level, realizes accurate prediction of power grid situation risk level, and effectively avoids accidents caused by excessively high risk level in the power grid.

This invention discloses a health assessment method and apparatus for a high-temperature aging test chamber for integrated circuits, belonging to the field of integrated circuit technology. The method includes: determining the health value of each module in the test chamber and calculating the degradation rate of each module based on the health value; constructing a coupling influence relationship matrix based on the number of modules in the test chamber and the influence coupling coefficient between modules; generating a dynamic weight vector corresponding to the test chamber based on the health value of each module, degradation rate, predefined benchmark weight vector, and the coupling influence relationship matrix; constructing a fuzzy relationship matrix for health levels; generating a comprehensive health evaluation vector based on the dynamic weight vector and the fuzzy relationship matrix for health levels; and determining the target health value of the test chamber based on the comprehensive health evaluation vector and the health score of the test chamber under each evaluation level. This scheme makes the obtained health assessment results more accurate and more consistent with physical reality.

The invention discloses an energy transformation index quantification method based on power data comprehensive evaluation integration, and the method is mainly used in the field of energy transformation evaluation, such as energy policy making, energy investment decision making, energy technology development direction and the like. The method comprises the following steps of: constructing an index system; solving a weight by using CRITIC-BWM; and performing fuzzy comprehensive evaluation. The method comprises the following steps: S1, when an index system is constructed, from four dimensions of an energy supply structure, electric power cleaning, policy support and economic benefits, refining twelve secondary indexes such as a renewable energy source ratio, a traditional energy source ratio, an energy self-sufficiency rate and the like; s2, calculating the weight by using the CRITIC-BWM method, namely calculating an objective weight by using a CRITIC method and calculating a subjective weight by using a BWM method, and finally carrying out weight synthesis; and S3, fuzzy comprehensive evaluation comprises two steps of fuzzy set construction and fuzzy comprehensive model evaluation, and the final evaluation grade of the energy transformation index is determined and the influence of each index is analyzed by calculating the index membership degree, constructing a fuzzy relation matrix and combining a final weight vector with the fuzzy relation matrix.

The invention discloses a power energy type selection method, device and system of an inland ship, a storage medium and a computer program product, and belongs to the technical field of inland ship engineering.The method comprises the steps that an evaluation index set and alternative power energy types are determined, qualitative evaluation information of all indexes is converted into a fuzzy relation matrix based on the fuzzy mathematical theory, and the fuzzy relation matrix is calculated; and calculating the weight value of each index by adopting an entropy weight method, performing fuzzy synthesis operation in combination with the weight value and the fuzzy relation matrix, normalizing the result, and finally determining the adaptive target power energy type by solving the total score of evaluation and calculating the relative proximity of each alternative type and the optimal solution. According to the scheme, quantification, comprehensiveness and precision of inland ship power energy selection are achieved.

The present invention discloses a multidimensional diagnostic evaluation method and device for auxiliary equipment of a pumped-storage power station. The method and device establish evaluation indicators and grades for each key component of each auxiliary equipment in the pumped-storage power station, collect operating data of each key component of each auxiliary equipment, evaluate each evaluation indicator of each key component according to the operating data, evaluation indicators and grades, and obtain a fuzzy relationship matrix; determine the weight of each evaluation indicator, obtain a fuzzy comprehensive evaluation result vector of each key component according to the fuzzy relationship matrix and the weight, further determine the health status of each key component, and determine the first health status of each auxiliary equipment through priority; obtain fault diagnosis data of each auxiliary equipment in the equipment system of the pumped-storage power station, determine the second health status of each auxiliary equipment according to the fault diagnosis data, and obtain the health status of each auxiliary equipment through priority determination based on the first health status and the second health status.

The invention provides a construction project risk prediction and decision optimization method and system based on AI, and relates to the field of construction project risk prediction, and the method comprises the steps: decomposing a construction project into a plurality of stages, recognizing the risk factors of each stage, constructing a multi-level risk index system, determining the weight of each index, forming a fuzzy relation matrix, and determining the risk level. And a corresponding risk coping strategy is generated, and effective prediction and decision optimization of the construction project risk are realized.