摘要： 直觉模糊软集不能处理参数的隶属度与非隶属度之和大于1的情况,使决策过程受限,影响其应用范围。针对该问题,结合毕达哥拉斯模糊集的特性与软集的参数化,构造毕达哥拉斯模糊软集。介绍毕达哥拉斯模糊软集的补、并、交、且、或、加、乘、必须、可能等运算,给出运算结果,并讨论其德摩根定律。设计基于毕达哥拉斯模糊整合算子的决策算法,分析该算法的计算复杂度,并将其应用到股票投资,应用结果证明了该算法的有效性。

关键词: 毕达哥拉斯模糊软集, 整合算子, 德摩根定律, 计算复杂度, 股票投资

Abstract: In order to solve the problem that intuitionistic fuzzy soft set can not deal with the situation that the sum of membership degree and non-membership degree of the parameter is bigger than 1.It makes the decision processs limted,and affects the application range.This paper combines the characteristics of Pythagorean fuzzy set with the parameterization of soft set,and constructs Pythagorean fuzzy soft set.Some operations such as complement,union,intersection,and,or,addition,multiplication,necessity,and possibility are defined.Some corresponding results are presented,and the De Morgan’s Law of Pythagorean fuzzy soft sets are discussed in detail.A decision making algorithm based Pythagorean fuzzy aggregation operator is proposed.This paper analyses the computational complexity of this algorithm,and applies it to stock investment.Experimental results show that the algorithm is effectiveness.

Key words: Pythagorean fuzzy soft set, aggregation operator, De Morgan’s law, computational complexity, stock investment

中图分类号: 

• TP301