A new interpolative reasoning method in sparse rule-based systems

✍ Scribed by Wen-Hoar Hsiao; Shyi-Ming Chen; Chia-Hoang Lee

• Publisher: Elsevier Science
• Year: 1998
• Tongue: English
• Weight: 374 KB
• Volume: 93
• Category: Article
• ISSN: 0165-0114
• DOI: 10.1016/s0165-0114(96)00190-x

✦ Synopsis

In , Yan et al. analyzed Koczy and Hirota's linear interpolative reasoning method presented in I-2, 3] and found that the reasoning consequences by their method sometimes become abnormal fuzzy sets. Thus, they pointed out that a new interpolative reasoning method will be needed which can guarantee that the interpolated conclusion will also be triangular-type for a triangular-type observation. In this paper, we extend the works of to present a new interpolative reasoning method to deal with fuzzy reasoning in sparse rule-based systems• The proposed method can overcome the drawback of Koczy and Hirota's method described in . It can guarantee that the statement "If fuzzy rules A 1 ~B1, A 2 ~B 2 and the observation A* are defined by triangular membership functions, the interpolated conclusion B* will also be triangular-type" holds.