Robustness of interval-valued fuzzy inference

Authors:
De-chao Li;Yong-ming Li;Yong-jian Xie
Affiliations:
School of Mathematics, Physics and Information Science, Zhejiang Ocean University, Zhoushan 316000, China;College of Computer Science, Shaanxi Normal University, Xi'an 710062, China;College of Mathematics and Information Science, Shaanxi Normal University, Xi'an 710062, China
Venue:
Information Sciences: an International Journal
Year:
2011

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Abstract

Since interval-valued fuzzy set intuitively addresses not only vagueness (lack of sharp class boundaries) but also a feature of uncertainty (lack of information), interval-valued fuzzy reasoning plays a vital role in intelligent systems including fuzzy control, classification, expert systems, and so on. To utilize interval-valued fuzzy inference better, it is very important to study the fundamental properties of interval-valued fuzzy inference such as robustness. In this paper, we first discuss the robustness of interval-valued fuzzy connectives. And then investigate the robustness of interval-valued fuzzy reasoning in terms of the sensitivity of interval-valued fuzzy connectives and maximum perturbation of interval-valued fuzzy sets. These results reveal that the robustness of interval-valued fuzzy reasoning is directly linked to the selection of interval-valued fuzzy connectives.