Robustness of full implication algorithms based on interval-valued fuzzy inference

被引：34
|
作者：
Luo, Minxia [1 ]
Zhang, Kai [1 ]
机构：
[1] China Jiliang Univ, Dept Math, Hangzhou 310018, Peoples R China
来源：
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING | 2015年 / 62卷
基金：
中国国家自然科学基金;
关键词：
Interval-valued fuzzy set; Interval-valued fuzzy inference; Triple I algorithm; Robustness; Interval-valued fuzzy connectives; T-NORMS; LOGIC FOUNDATION; REPRESENTATION; OPERATORS; SYSTEMS; DESIGN;
D O I：
10.1016/j.ijar.2015.05.006
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a new full implication algorithm based on interval-valued fuzzy inference which extends the triple I principle for fuzzy inference based on fuzzy modus ponens and fuzzy modus tollens to the case of interval-valued fuzzy sets is presented. We first give the corresponding interval-valued R-type triple I solutions and then investigate the robustness of triple I algorithms based on interval-valued fuzzy sets for fuzzy inference. The sensitivity of some special algorithms based on four important interval-valued residuated implication is given. It is shown that the robustness of interval-valued full implication algorithms for fuzzy inference directly depends on the selection of interval-valued fuzzy connectives. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码：61 / 72
页数：12
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