Robustness of Fuzzy Reasoning Based on Schweizer-Sklar Interval-valued t-Norms

被引：7

作者：

Luo, Min-Xia ^{[1
]}

Cheng, Ze ^{[1
]}

机构：

[1] China Jiliang Univ, Dept Math, Hangzhou 310018, Zhejiang, Peoples R China

来源：

FUZZY INFORMATION AND ENGINEERING | 2016年 / 8卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Schweizer-Sklar interval-valued operator; Interval-valued fuzzy connective; Interval-valued fuzzy inference; Robustness;

D O I：

10.1016/j.fiae.2016.06.004

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we focus on the parametric triple I algorithms by the combination of Schweizer-Sklar interval-valued operators and triple I principles for fuzzy reasoning. Firstly, we give the interval-valued triple I solutions based on Schweizer-Sklar interval-valued operators. Then, we investigate the sensitivity of Schweizer-Sklar interval-valued fuzzy connectives. Finally, we study the robustness of the triple I algorithms based on Schweizer-Sklar interval-valued t-norms (m is an element of (0,infinity)). It shows that the quality of interval-valued fuzzy reasoning algorithms depends on the selection of interval-valued fuzzy connectives.

引用

页码：183 / 198

页数：16

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