Fuzzy entropy functions based on perceived uncertainty

被引：0

作者：

Aggarwal, Manish ^{[1
]}

机构：

[1] Indian Inst Technol Jodhpur, Sch Artificial Intelligence & Data Sci, Jodhpur, Rajasthan, India

来源：

KNOWLEDGE AND INFORMATION SYSTEMS | 2022年 / 64卷 / 09期

关键词：

Fuzzy entropy; Uncertainty; Decision-making; Perceived uncertainty; Agent; Probabilistic fuzzy; DISTANCE MEASURE; DECISION-MAKING; SETS; DEFINITION;

D O I：

10.1007/s10115-022-01700-w

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The paper presents fuzzy entropy functions based on perceived vagueness. The proposed entropy functions are based on the principle that different agents may perceive a membership grade differently. The perceived uncertainty for a membership grade is determined through a gain function. In this light, new variants of the popular fuzzy entropy functions are developed. Inspired by these variants, a novel fuzzy entropy function is also developed. The proposed functions are extended to the probabilistic fuzzy domain. A case study is included to illustrate applicability of the work.

引用

页码：2389 / 2409

页数：21

共 39 条

[1] Attitude-based entropy function and applications in decision-making [J].