57 results about "TOPSIS" patented technology

The invention discloses a multi-objective optimization water resource allocation scheduling method, which combines an LSTM-Prophet hybrid prediction model with an attention mechanism, synchronously captures climate periodicity, policy regulation sensitivity and industrial development tendency characteristics in water demand prediction, and improves water demand prediction precision through a genetic algorithm. Through an improved NSGA-III algorithm and a PSO collaborative optimization mechanism, the convergence problem of a high-dimensional target space is effectively solved in combination with a chaotic mapping technology, and the multi-target optimization efficiency is improved by 40% in cooperation with a dynamic weight adjustment strategy of deep reinforcement learning. And multi-scenario simulation verification of a scheduling scheme is realized by utilizing deep coupling of a digital twin system and a three-dimensional GIS, and a real-time feedback correction mechanism of a Markov decision process is realized. A finally constructed entropy weight-TOPSIS multi-dimensional evaluation system is combined with AR visualization and intelligent contract traceability technologies, and a Pareto optimal solution giving consideration to social fair, economic benefits and ecological integrity is provided for decision makers.

The invention provides a laser remelting process parameter optimization method and system based on a multi-objective optimization algorithm. The method comprises the steps that the range of laser remelting process parameters on the surface of a cladding layer is limited; designing a process parameter combination by using an ELHS method, carrying out a laser remelting experiment by using different process parameter combinations on the premise of keeping the surface quality of the cladding layer consistent, and collecting performance index data after remelting; establishing a nonlinear mapping model between the process parameters and the performance indexes by using a PSO-XGBoost model; a Pareto optimal solution set is obtained through population and individual initialization, non-dominated sorting, congestion degree calculation, optimal solution calculation and global optimization of process parameters by adopting an MOEDO algorithm based on a nonlinear mapping model; and a CRITIC-TOPSIS decision system is utilized to carry out evaluation sorting on the Pareto optimal solution set, and an optimal process parameter combination is screened out. According to the method, the influence of the laser power, the scanning speed and the lap joint rate on the quality and performance of the laser remelting surface can be considered at the same time, and the limitation of traditional single process parameter optimization is broken through.

The invention discloses a multi-objective optimization method for improving the comprehensive performance of a hydrostatic guideway, and the method comprises the steps: 1, carrying out the theoretical analysis and calculation of the performance indexes of the hydrostatic guideway based on a hydrostatic bearing theory, obtaining a mathematical model of each performance index, and determining design parameters which affect the working performance of the hydrostatic guideway; step 2, on the basis of a Sobol sensitivity analysis method, obtaining sensitivity indexes of each design parameter on the comprehensive performance of the hydrostatic guideway, determining key design parameters with relatively great influence, and analyzing an influence rule of each key design parameter on the performance of the guideway; and step 3, based on an NSGA-II multi-objective optimization algorithm, constructing a hydrostatic guideway comprehensive performance multi-objective optimization model, and obtaining a Pareto optimal solution set. And step 4, based on an AHP-TOPSIS method, selecting an optimal optimization scheme of the hydrostatic guideway in a Pareto optimal solution set obtained through a targeted optimization algorithm.

The invention provides a CORS network data quality evaluation method based on entropy weight TOPSIS. The method comprises the following steps: S-1, forming an original matrix; s-2, standardizing the xij to obtain a standardized Zij (Zij); s-3, calculating the proportion of the index j corresponding to the object i in the column sum; s-4, calculating an entropy value of an index j corresponding to the object i; s-5, calculating a difference coefficient of the jth index; s-6, calculating the weight of the jth index; s-7, multiplying the weight point calculated in the step S6 by the standardized matrix to obtain a weighted standardized matrix; s-8, positive and negative ideal solutions are determined; s-9, calculating an Euclidean distance; s-10, finally calculating a comprehensive score Si of the base station in the ith CORS network; and S-11, judging the final advantages and disadvantages of all the reference stations of the current CORS station network according to the score. The GNSS and CORS data quality evaluation method combines observation data acquired by a CORS station network in real time or after the event and entropy weight TOPSIS with objectivity, comprehensiveness and high efficiency as core advantages, and provides quality evaluation for GNSS and CORS data.

The invention belongs to the technical field of material type selection, and particularly discloses an improved TOPSIS material type selection method and system based on information entropy, and the method comprises the steps: calculating the information entropy of each attribute of a material, and obtaining a weight coefficient of each attribute; adopting a TOPSIS method, determining positive and negative ideal solutions based on the weight coefficient, calculating the distance between each to-be-selected material scheme of the structure and the fuzzy positive and negative ideal solutions, further obtaining a relative close degree, and determining an optimal material scheme according to the relative close degree; wherein the calculation method of the positive and negative ideal solutions comprises the following steps: constructing a weighted standardized matrix according to a weight coefficient, then calculating the standard deviation of each attribute according to the weighted standardized matrix, and introducing a triangular fuzzy number to construct and obtain the fuzzy positive and negative ideal solutions. The method effectively improves scientificity and reliability of material type selection, is suitable for optimal decision-making of multi-attribute materials under complex working conditions, and particularly has remarkable advantages in lightweight design in the fields of automotive engineering and the like.

The application provides a processing parameter optimization method based on a GRA-CRITIC-TOPSIS method and processing surface integrity multi-indexes, and belongs to the technical field of high-efficiency precision processing. In view of the problems that the influence of processing parameters on workpiece surface integrity multi-indexes is complex in difficult-to-machine material milling processing, and the expected results of various indexes are contradictory, the grey correlation analysis method (GRA), the CRITIC objective weighting method and the ideal point method (TOPSIS) are organically combined, and a more scientific and comprehensive multi-objective processing parameter comprehensive optimization model is constructed. The method introduces the CRITIC objective weighting, the weight calculation is more reasonable, the index information overlap can be effectively avoided, and the optimization result has higher engineering reliability.

This invention provides a general optimization method and system for water supply scheduling of parallel reservoir groups. By acquiring system operation data of the parallel reservoir group and its water supply network, a multi-level, multi-attribute generalized directed graph model is constructed. Based on this model, the dynamic operating state of the water resource network is dynamically generalized, and multiple objective functions and constraints are dynamically configured. Simultaneously, scheduling decision variables are identified and the degree of constraint violation is quantified, forming a generalized optimization problem definition. Different optimization algorithms are supported, and the optimization problem is solved in multiple cycles through a scheduling decision evaluation module. The TOPSIS method is used to select representative solutions, obtaining the optimal release decision for each reservoir in each scheduling cycle. Finally, the performance of the scheduling scheme is evaluated based on simulation results, and a detailed operation report is generated. This invention can effectively improve the scientific and economic efficiency of water supply scheduling of parallel reservoir groups, providing important technical support for regional water resource optimization scheduling and refined management.

The invention relates to a transducer index evaluation method based on TOPSIS multi-objective optimization, and the method comprises the following steps: S1, carrying out the response test of a transducer according to an optimization variable in an anechoic pool, and obtaining test data; s2, processing the test data based on a TOPSIS multi-objective optimization algorithm to obtain an optimization result; and S3, based on the optimization result, determining the optimal installation position of the transducer in the fairing, and completing transducer index evaluation. According to the invention, through combination of the multi-dimensional test and the multi-objective optimization algorithm, global optimal selection of the installation position of the transducer is realized, and the problems of dependence on experience and incomplete optimization in the prior art are solved.

The invention discloses a ship type multi-objective optimization decision-making method based on AHP and TOPSIS, and relates to the technical field of multi-objective optimization. Selecting a mother type ship, and taking wave-making resistance, heaving amplitude and pitching angle as targets of ship type hydrodynamic performance evaluation; carrying out numerical forecasting on wave-making resistance, heaving amplitude and pitching angle target values of the mother ship; setting a ship type position to be modified, a design variable of ship type transformation and a constraint range of the variable; generating a sample ship type similar to the mother type ship; calculating wave-making resistance, heaving amplitude and pitching angle target value of each sample ship type; and taking the target value as an optimization design objective function, combining AHP and TOPSIS as an objective function evaluation method, and taking a non-dominated sorting genetic algorithm NSGA-II as a multi-objective optimization algorithm to search in a ship type space to obtain a ship type corresponding to a multi-objective optimization optimal solution. According to the method, the ship type optimization design efficiency is improved.

The invention discloses a multi-dimensional electric power market operation effect evaluation method and system, and relates to the technical field of electric power market operation effect evaluation, and the method comprises the steps: constructing a multi-dimensional index system covering the core operation dimension of an electric power market, and according to a combined weighting model composed of a fusion analytic hierarchy process and an entropy weight method, carrying out the evaluation of the operation effect of the electric power market; subjective experience and objective data are combined; and calculating the distance between each province and an ideal solution according to the combined data by using a TOPSIS model to realize comprehensive sorting, and processing uncertainty through fuzzy logic and Bayesian reasoning to complete evaluation of the multi-dimensional power market operation effect. According to the method, subjective experience and objective data are fused through combined empowerment, inter-provincial multi-index comprehensive sorting is realized by means of TOPSIS, risk causal reasoning is performed by using a fuzzy Bayesian network (FBN), a complementary closed loop of'macroscopic sorting-microscopic diagnosis' is formed, and the blank in the field of provincial power market dynamic evaluation and risk traceability in the prior art is filled.

The invention provides a logistics industry green innovation performance spatio-temporal heterogeneity analysis method, which comprises the following steps of: 1, constructing a multi-dimensional index system, and calculating a logistics industry green innovation performance comprehensive index through a combined weighting method and a TOPSIS method; 2, coupling the weight matrixes of the geography, economy and logistics networks, and constructing a spatial weight matrix; step 3, analyzing a space driving mechanism of logistics industry green innovation performance by using an improved space Durbin model (SDM), and decomposing space effects into four classes of instant / accumulation and direct / indirect; and 4, constructing a space Markov chain model by taking a space lag factor as a condition, and realizing dynamic prediction and club convergence detection of a logistics industry green innovation performance state. According to the method, thoughts and schemes are provided for solving the problem that static evaluation and dynamic prediction are separated in traditional research, an evaluation-mechanism-prediction framework is formed, and accurate support is provided for formulating regional logistics policies.

The invention relates to an equipment transformation priority determination method and system based on an improved Sougee optimization algorithm, and the method comprises the steps: firstly constructing an evaluation index system used for reflecting the equipment transformation priority, then calculating a comprehensive weight, and carrying out the optimization based on a multi-objective optimization improved Sougee optimization algorithm to obtain an optimal comprehensive weight; and finally, a TOPSIS method based on DBSCAN-AGNES double clustering redefinition is adopted to calculate and obtain the closeness degree and sort the closeness degree so as to determine the transformation priority of the old production equipment of the power grid. According to the method, subjective and objective weights are calculated in combination with the AHP and the improved CRITIC method, the dynamic crowding speed and the global-local search mechanism are introduced to improve the South goose optimization algorithm, intelligent optimization of the weights is achieved, weight distribution is more accurate and reasonable, meanwhile, based on DBSCAN-AGNES dual clustering, the problem that a traditional TOPSIS method is interfered by abnormal values and noise is avoided, and the method is suitable for large-scale popularization and application. And the robustness and reliability of the evaluation result are improved, so that the equipment transformation priority can be determined more scientifically and accurately.

The invention discloses an internal income comprehensive distribution method, system and device capable of adjusting load after large-scale aggregation and a storage medium, and relates to the technical field of energy optimization scheduling and energy management, and the method comprises the steps: constructing a comprehensive contribution index system based on safety, economy and risk indexes; outputting the comprehensive contribution degree of each load resource according to the comprehensive contribution degree index system by adopting a comprehensive evaluation method fusing TOPSIS, grey correlation and an entropy weight method; creating an energy-auxiliary service market joint income model, and quantifying the value contribution of the adjustable load polymer; and according to the comprehensive contribution degree of each load resource and the energy-auxiliary service market joint income model, performing internal income distribution by using a double-layer settlement framework of fixed protocol electricity price and contribution degree assessment. According to the method, a comprehensive contribution degree model based on safety, economy and risk indexes is constructed, TOPSIS grey correlation and an entropy weight method are fused, and accurate quantification and fair distribution of load resource values are achieved.

The invention provides a friction damper multi-target parameter intelligent optimization and decision-making system and a friction damper multi-target parameter intelligent optimization and decision-making method. The system comprises a data input module, a hyper-parameter automatic configuration module, a high-performance CNN proxy model construction module, a Pareto solution set search module, an entropy weight TOPSIS decision module and a result output module. The invention further relates to a method of the friction damper multi-target parameter intelligent optimization and decision making system. According to the method of the friction damper multi-target parameter intelligent optimization and decision-making system, a high-performance CNN proxy model is automatically constructed by adopting Bayesian optimization, and the problems of multi-target optimization and scheme optimization of complex parameters of the friction damper are efficiently and objectively solved in combination with NSGA-II multi-target optimization and an entropy weight TOPSIS intelligent decision-making mechanism, so that the method has the advantages that the method is simple and convenient, and the efficiency is high. And the optimization efficiency and the decision reliability are obviously improved.

The invention provides a thermal storage performance optimization method and device based on solid-state hydrogen storage, and relates to the technical field of solid-state hydrogen storage, and the method comprises the steps: constructing a solid-state hydrogen storage device finite element model containing heat-mass-momentum transmission multi-physics field coupling; analyzing the influence level of the to-be-optimized parameters of the spiral heat exchange tube on the heat storage performance by adopting a Taguchi method; and generating a Pareto frontier solution set through a non-dominant sorting second-generation genetic algorithm, constructing a multi-target evaluation matrix based on weighted grey relational degree analysis, and performing secondary screening by adopting an approximate ideal solution sorting method to determine an optimal parameter combination. According to the method, a multi-physics field coupling simulation model is constructed, a two-stage optimization architecture of a non-dominant sorting second-generation genetic algorithm and an approximate ideal solution sorting method is adopted, and collaborative optimization of spiral pipe parameters and fluid dynamic parameters is achieved. Key factors are pre-screened through a Taguchi method, a three-dimensional evaluation matrix is established in combination with grey correlation analysis, and balanced optimization of reaction scores and outlet temperature is ensured.

The application claims a data integrity audit matching method based on psychological perception and preference, comprising the following steps: S1: calculating the subjective and objective weights of each evaluation index, and calculating the subjective and objective combination weights of the index based on the weights, and then calculating the weight of each audit scheme by using the improved Topsis comprehensive evaluation method; S2: calculating the user preference weight by using the triangular fuzzy number and Topsis method according to the user preference set, and integrating the weights of the two; S3: quantitatively calculating the comprehensive preference value of both parties according to the demand preference of the audit task and the execution preference of the audit resource, and calculating the preference utility value matrix of both parties; S4: calculating the perception utility value matrix of both parties based on the improved disappointment theory; S5: standardizing the perception utility value matrix, taking the maximization of the standard perception utility value of both parties as the optimization goal, constructing a double-objective optimization model, and solving the model. The application effectively improves the comprehensive satisfaction of both parties in the case of considering the psychological factors and preferences of both parties.

The invention discloses a dynamic evaluation and prediction method and system for low-carbon economic development benefits in the building industry, and relates to the technical field of low-carbon economic evaluation and prediction. The method comprises the following steps: S1, data acquisition and preprocessing; s2, determining an index weight based on a variable coefficient method; step S3, carrying out dynamic evaluation based on a GRA-TOPSIS model; step S4, checking modeling data; s5, constructing and predicting an equal-dimension gray number progressive complement GM (1, 1) model; and S6, verifying the model precision and outputting a result. According to the method, an evaluation system is constructed based on 15 three-dimensional indexes of social benefits, economic benefits and ecological benefits, a benefit evolution rule in a time dimension is captured in combination with a GRA-TOPSIS model, short-term impact and long-term influence of policy adjustment and external emergencies on low-carbon development of the building industry are accurately reflected, an evaluation result is more in line with an actual development situation, and the method is suitable for popularization and application. And multi-dimensional dynamic evaluation is realized, and the limitation of traditional static analysis is broken through.

A transmission line fault prediction system based on multi-algorithm fusion includes a data acquisition module, an entropy weight-TOPSIS evaluation module, an ARIMA prediction module, a dynamic weight adjustment module, a closed-loop feedback optimization module, a risk level classification module, and a decision support and visualization platform. The system standardizes multi-source data using the entropy weight-TOPSIS evaluation model, calculates the information entropy and weight of each indicator, and derives a line health status score. The ARIMA prediction module predicts the fault probability based on the evaluation results and time-series data. The dynamic weight adjustment module dynamically adjusts the ARIMA model parameters according to the health status score. The closed-loop feedback optimization module compares the prediction results with actual fault data and continuously optimizes the model parameters. The risk level classification module outputs four-level risk warnings based on the fault probability and health status score. The decision support and visualization platform generates inspection suggestions, maintenance priority ranking, and route optimization schemes, and supports GIS map display.

This invention relates to a transducer performance evaluation method based on TOPSIS multi-objective optimization, comprising the following steps: Step S1, conducting response tests on the transducer in an anechoic water tank according to optimization variables, and obtaining test data; Step S2, processing the test data based on the TOPSIS multi-objective optimization algorithm to obtain optimization results; Step S3, determining the optimal installation position of the transducer in the fairing based on the optimization results, thus completing the transducer performance evaluation. This invention, through the combination of multi-dimensional testing and multi-objective optimization algorithms, achieves globally optimal selection of the transducer installation position, solving the problems of reliance on experience and incomplete optimization in existing technologies.

The invention provides an enterprise organization adjustment evaluation method and system based on transverse and longitudinal comparison, and the evaluation method is applied to an evaluation system comprising an index selection module, a data processing module, a data analysis module and an evaluation module, and specifically comprises the steps: constructing a multi-dimensional evaluation index system based on a preset dimension, index data of each to-be-evaluated object in enterprise organization adjustment is extracted and preprocessed; calculating the information entropy and the difference coefficient of each evaluation index, determining the corresponding objective weight, and constructing a weighted evaluation matrix, thereby calculating the positive and negative ideal solutions of the indexes, obtaining the corresponding close degree of each object to be evaluated, and obtaining the enterprise organization adjustment evaluation result through the synchronization comparison of multiple objects to be evaluated and the time sequence comparison of a single object to be evaluated. According to the method, quantitative evaluation of different evaluation objects is realized in combination with the entropy weight and the TOPSIS method, and accurate evaluation of the enterprise organization adjustment effect is realized through transverse and longitudinal comparison of a multi-object synchronization time sequence and a single-object time sequence.

The invention provides a rolling bearing fault risk evaluation method and system based on picture fuzzy multi-attribute decision, and belongs to the field of bearing fault risk evaluation. The method aims at solving the problems that in the picture fuzzy environment, a traditional attribute reduction algorithm is difficult to fully mine the nonlinear relation between attributes, the reduction efficiency is low, the reduction precision is poor, and the robustness is poor. According to the unsupervised attribute reduction algorithm based on the Gaussian kernel function, an attribute self-expression function and a triple regularization mechanism are fused; and the method is fused with TOPSIS, and is used for solving the complex fuzzy multi-attribute decision problem that the neutral attitude needs to be clearly expressed in a picture fuzzy set environment. Experimental results show that the GKFUAR-TOPSIS method not only maintains the decision accuracy, but also has the decision rate significantly superior to that of other traditional decision methods suitable for the problem.

The invention discloses a coal-electricity transformation path comprehensive evaluation method and system based on AHP-TOPSIS, and relates to the field of power system planning, and the method comprises the steps: constructing a multi-dimensional index system for evaluating a coal-electricity transformation path based on an environment dimension, a system dimension and an economic dimension, and giving an index weight through an analytic hierarchy process AHP; and on the basis of a multi-dimensional index system with index weights, alternative scheme sorting is carried out through an approximate ideal solution sorting method TOPSIS, and comprehensive evaluation is carried out on a coal-electricity transformation path. Through organic combination of AHP and TOPSIS, subjective judgment and objective data information are effectively fused, scientificity, systematicness and operability of comprehensive evaluation of the coal-electricity transformation path are improved, and more reliable decision support is provided for energy planning and policy making.

This invention belongs to the field of composite material structure optimization design technology, and discloses an integrated design method for composite material pipe winding parameters based on surrogate models and multi-objective optimization. The steps include: First, through parametric modeling and automated finite element simulation, a rapid mapping from design variables to performance responses is achieved; second, samples are generated based on optimal Latin hypercube sampling, and a high-precision Kriging surrogate model is constructed to replace time-consuming high-fidelity simulation; third, using the surrogate model as an evaluation tool, the NSGA-II multi-objective genetic algorithm is used for optimization, obtaining a series of Pareto optimal solution sets that achieve the best trade-off among multiple performance objectives; finally, the entropy weight method is used to objectively calculate the weights of each performance index, and the TOPSIS method is combined to make a comprehensive decision on the Pareto solution set, selecting the final optimal parameter combination. This achieves efficient, high-precision, and automated multi-objective optimization design of composite material pipe winding parameters, and ensures the comprehensive optimality and objectivity of the design scheme.

The invention discloses an optimization method for a high and large aqueduct group complex decision problem based on an AHP-FCE-TOPSIS comprehensive model, and relates to the field of hydraulic engineering, and the method comprises the steps: S1, building an evaluation index system; s2, performing pairwise comparison on the evaluation indexes in the index layer by using an analytic hierarchy process, and calculating a weight vector W of each evaluation index in the criterion layer or the index layer by constructing a judgment matrix; s3, performing fuzzy evaluation on the performance of each scheme in the scheme layer under the evaluation index by using a fuzzy comprehensive evaluation method, and constructing a membership matrix R; s4, multiplying the membership matrix R by the weight vector W to obtain a weighted fuzzy evaluation matrix F; s5, determining an ideal solution and a negative ideal solution of the weighted fuzzy evaluation matrix F by using an approximate ideal solution sorting method; calculating the relative closeness of each scheme to the ideal solution and the negative ideal solution; and sorting the schemes according to the relative proximity, and outputting a sorting result to complete decision optimization. And the scientificity, accuracy and reliability of complex decision making are comprehensively improved.

The invention discloses a scientific and technological achievement conversion effect deduction method considering a dissipation structure, and relates to the technical field of achievement conversion evaluation. The method comprises the steps of obtaining scientific and technological achievement transformation evaluation indexes and performing preliminary screening to obtain candidate indexes; determining a third-level index, a second-level index and a first-level index; using an entropy weight method and a TOPSIS method to calculate and obtain data of a second-level index and a first-level index; constructing a dissipation evolution model; judging whether the scientific and technological achievement conversion system can form a dissipation structure or not, if the dissipation structure can be formed, keeping the evaluation index of the scientific and technological achievement conversion system unchanged, and otherwise, adjusting the evaluation index of the scientific and technological achievement conversion system. It can be seen that by judging whether the scientific and technological achievement transformation system can form the dissipation structure or not, it can be determined that the evaluation indexes of the scientific and technological achievement transformation system are suitable and reasonable, and then data support and reference basis are provided for making of scientific and technological achievement transformation policies and resource configuration.

A cable accessory installation personnel capability comprehensive evaluation method based on improved combination empowerment-TOPSIS comprises the steps that cable accessory installation personnel training regulations and standard files are analyzed, and evaluation indexes are determined; establishing a comprehensive evaluation index system; comparing the importance of each evaluation index by using an analytic hierarchy process to obtain a judgment matrix, and obtaining a subjective weight vector of each evaluation index; key behavior data of different persons are collected, and normalization processing is carried out on the key behavior data; obtaining objective weights of the evaluation indexes; performing combination optimization on the subjective weight and the objective weight to obtain a final comprehensive weight; the Euclidean distance between each evaluated object and the ideal solution is calculated, and then the close degree coefficient of the evaluated object is calculated; and sorting all the evaluation objects according to the closeness, and outputting a final grade evaluation result according to a preset score interval. According to the evaluation method, a subjective and objective weight optimization mechanism and a TOPSIS multi-attribute decision model are fused, and the capability quality of cable accessory installation personnel is scientifically, quantitatively and comprehensively evaluated.

The application discloses a decision-level multi-model dynamic fusion classification method, and steps are as follows: establishing each base model and obtaining a data set containing samples and real classification categories, obtaining a predicted classification category through base model prediction, calculating classification accuracy in combination with the real categories and constructing a matrix; converting the predicted classification category into a one-hot encoding form to obtain a voting matrix; after filtering the constructed matrix, the contribution weight of each base model is calculated by using the TOPSIS method; the voting matrix and the weight are multiplied by a scalar to obtain an effective category voting weight matrix, and after element-wise Hadamard product, a two-dimensional matrix of the voting fusion classification category of all samples is generated through matrix addition, and finally the two-dimensional matrix is processed to obtain the fusion classification category. The application aims at the problem that the performance of the existing fusion classification method depends on the sample data quality, dynamically selects the advantage base model and the category which is good at prediction, and dynamically assigns the weight, so that more accurate fusion classification is realized.

The invention belongs to the technical field of steam and roller skating oil pump spare part importance degree evaluation, discloses a steam and roller skating oil pump spare part importance degree evaluation method based on TOPSIS analysis, and aims at solving the problems that steam and roller skating oil pump spare parts are multiple in variety, spare part reserve influence factor degrees are multiple, and spare part reserve decision making difficulty is large. The spare part reserve variety is preliminarily determined based on maintenance work analysis, a spare part importance degree evaluation index system is constructed on the basis of research and analysis of steam and roller skating oil pump spare part importance degree influence factors, and spare part importance degree evaluation is performed by adopting a TOPSIS analysis method. When the TOPSIS analysis method is used, an analytic hierarchy process and an entropy weight method are combined to determine the index weight, subjective and objective weights are combined to make up for the respective insufficiency of the two methods, and a satisfactory result is obtained. The method can provide reference for spare part reserve optimization of other equipment, and can also provide thoughts for other multi-attribute decision-making problems.

This invention discloses a method and system for determining design schemes for urban engineering projects. The method involves acquiring design information for each scheme and calculating its information density index; obtaining subjective evaluation indicators and objective performance indicators; determining subjective weights using fuzzy hierarchical analysis and extracting objective weights using CRITIC; and performing a game-theoretic equilibrium fusion of the subjective and objective weights to obtain a weight decision matrix for each design scheme. When the information density index is not less than a preset information density threshold, the method calculates annual photovoltaic capacity indicators and annual building global warming potential, updating the weight decision matrix. Based on the weight decision matrix, the TOPSIS method is used to rank the design schemes. Using this invention, adaptive adjustments to decisions can be achieved during the design phase evolution, enabling an automatic switch from a subjective-objective integrated decision structure to a life-cycle objective performance-driven decision structure.

The invention discloses an aviation guarantee system efficiency evaluation method based on improved variable weight TOPSIS, and the method comprises the steps: building an aviation guarantee efficiency evaluation index system, building a judgment matrix according to the importance degree opinions between indexes, and calculating the constant weight of the indexes; the method comprises the following steps: based on an aviation guarantee efficiency evaluation index system, acquiring index data, standardizing the data to obtain an optimal value set and a worst value set of indexes, converting a projection value of a difference value between disadvantage information and advantage information of the indexes into an index dominance degree, and constructing an index dominance degree matrix; a state variable weight function is constructed, the efficiency evaluation result of the aviation guarantee system is calculated according to the relative closeness degree of each index and the absolute ideal solution, the aviation guarantee efficiency is remarkably improved through a dynamic adjustment mechanism, and therefore scientificity and adaptability are achieved.