Research On Large Problem Based On Mixed Information Research On Large-scale Fuzzy Multi-criteria Group Evaluation Problem Based On Mixed Information Criteria Group Evaluation

Aiming at the problems of non-homogeneity of evaluation information caused by the large number of evaluators,complex composition,and uneven evaluation levels in large-scale fuzzy multi-criteria group evaluations,difficulties in integrating evaluation matrices,and difficulties in selecting optimal solutions,this paper proposes The mixed information processing method based on the basic language term set,the evaluation matrix integration method,the determination method of the evaluation subject weight matrix,and the selection method based on the improved calmness optimal scheme are applied to the large-scale fuzzy multi-criteria group evaluation problem.First,a hybrid information processing method based on basic language term sets is proposed.Based on the description of the mixed information processing process,this paper discusses the characteristics and connections of the existing fuzzy evaluation data,the design of basic language term sets,the conversion methods of various types of mixed information,and the integration method of the membership function of mixed information to basic language term sets..It is divided into the following steps:(1)Analyze the structure of various common fuzzy numbers,classify fuzzy numbers according to structural characteristics,and select representative fuzzy numbers as examples for homogenization processing according to the classification results;(2)According to The "symbolic method" and "expansion principle" designed the basic language term set,taking the interval type II trapezoidal fuzzy number as its semantics;(3)Using the "number and shape combination" method to map various fuzzy numbers to the basic language term set,Obtain the membership functions of various fuzzy numbers to the basic language term set;(4)Define the generalized induced linguistic ordered weighting operator(GILOWA)based on interval closeness to integrate the membership functions,and the integration result is the interval binary linguistic number.Second,a method for determining the weight matrix of the evaluation subject,an integration method for the evaluation matrix,and a method for selecting the optimal solution based on improved calmness are proposed for large-scale fuzzy multi-criteria group evaluation.The steps are as follows:(1)Determine the weight matrix of the evaluation subject.First,the network is divided into several sub-communities based on the Louvain algorithm of the evaluator's social network application.Within the sub-community,the eigenvector centrality and degree centrality of the evaluator are calculated,and the geometric average of the two is used as the evaluator's "influence weight".Secondly,the certainty of the interval binary linguistic number is defined as the "understanding weight" of the evaluation subject to each evaluation object.In the same way,get the “weight of influence” and “weight of understanding” of the sub-community.Finally,the geometric average of the two weights is used as the evaluation subject weight matrix;(2)Integrate the evaluation matrix of the sub-community and use the VIKOR method to determine the evaluation result of the sub-community,write it in the form of a fuzzy set,and use the " The final evaluation results are obtained by the operations of “cross”,“union” and “geometric average”;(3)Define the improved calmness index.Measure the pressure faced when choosing the best solution.Numerical examples prove that all the methods proposed in this paper are feasible and reasonable.