Based On The Intuitive Normal Should Investigate The Number Of Fuzzy Multi-criteria Decision-making Method

There are a lot of fuzzy multi-criteria decision-making (FMCDM) problems in the social and economic activities. Many scholars have researched into the intuitionistic fuzzy multi-criteria decision-making problems, one important branch of FMCDM problems, and proposed some decision making methods. But, it’s difficult for the existed research to effectively solve a class of decision problems which are contain some information belong to normal distribution. However, in reality, a large number of natural phenomena and social phenomena belong to normal distribution. So the researches on these problems where some information belong to normal distribution have great significance.Based on summarizing and analyzing research achievements of predecessors and the definition of normal fuzzy number, the definition of the intuitionistic normal fuzzy number as well as its related concepts is given. Meanwhile, for multiple criteria decision making problems, in which the criteria values are intuitionistic normal fuzzy numbers, some approaches are proposed. Finally, the related definitions and decision methods are used in the evaluation and analysis of the investment value of stock. The main work and details are as follow:(1) Intuitionistic normal fuzzy numbers as well as their operational laws, score function, similarity measure and Euclidean distance formula is defined and the related properties of algorithms and distance formula are proved. Base on the present concepts, three classes of aggregation operators including intuitionistic normal fuzzy aggregation operators, intuitionistic normal fuzzy related aggregation operators, induced intuitionistic normal fuzzy aggregation operators as well as their related properties are defined. For multiple criteria decision making problems, in which the criteria values are intuitionistic normal fuzzy numbers and the criteria weight information is incomplete, an approach based on intuitionistic normal fuzzy aggregation operators is proposed. The optimal criteria weights are obtained by an optimal model based on the minimum of the sum of the distance between every two alternatives. And after aggregating criteria values by using intuitionistic normal fuzzy Aggregation operators, the comprehensive evaluation values of all alternatives can be gotten. Then, the ranking of the whole alternatives set can be obtained by comparing the relative closeness of alternatives to the ideal and anti-ideal solutions. For multiple criteria decision making problems, in which the criterion are interactive and the criteria values are intuitionistic normal fuzzy numbers, an approach based on induced intuitionistic normal fuzzy related aggregation operators is proposed. And after aggregating criteria values by using induced intuitionistic normal fuzzy related aggregation operators, the comprehensive evaluation values of all alternatives can be gotten. Then, the ranking of the whole alternatives set can be obtained by comparing the relative closeness of similarity measure of alternatives to the ideal solution.(2) Based on the analysis on the shortages of the existing score functions of intuitionistic fuzzy set, the factors that influence the shares of hesitation degree are divided into two cases. According to the two present different cases, two new different score functions called the prospect score function and the relative score function are defined. Base on the prospect value function, the prospect score function can better consider the influence on the decision makers from decision-making environment. Based on relative entropy, the relative score function consider the risk attitudes of the decision makers. Based on the present score functions, combined score function which can effectively synthesize the views of the two present score functions is also defined. Meanwhile, many examples have been given to show the validity of these score functions. In order to better adapt the three present score functions to solution of the intuitionistic normal fuzzy multi-criteria decision-making problems, it is equipped with an intuitionistic normal fuzzy extension. Finally, for the intuitionistic normal fuzzy multi-criteria decision-making problems in which criteria weights are fixed, and the criteria values of alternatives are in the form of intuitionistic normal fuzzy numbers, an intuitionistic normal fuzzy multi-criteria decision-making approach based on the score function is proposed.(3) Some definitions of the chapter III and chapter IV are used in the evaluation and analysis of the investment value of stock and an evaluation method of the investment value of stock is proposed. Firstly, six key indicators are determined by intuitionistic fuzzy set and the prospect score function. Secondly, based on the fact that most of the financial indicators belong to normal distribution, a method is given to change the index value into intuitionistic normal fuzzy numbers and a decision matrix can be obtained. Thirdly, after aggregating criteria values by using intuitionistic normal fuzzy aggregation operators, the comprehensive evaluation values of all stocks can be gotten. Finally, the ranking of the stocks can be obtained by similarity measure, and a comparative analysis has been made on the above results and the recent performance of stocks in the secondary market. Meanwhile, a comparative analysis has been made on the value of the new method and the existing method.