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
收藏
页码：183 / 198
页数：16
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