A Learning Algorithm for Distance-type Fuzzy Reasoning Method

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概要

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• We have already proposed a fuzzy reasoning method based on the distance between fuzzy sets. However, the distance type fuzzy reasoning method does not have a learning function. This paper discusses the benefits of providing the distance-type fuzzy reasoning method with a learning function. Unlike neural networks, GA, and other conventional approaches, this learning algorithm uses the features of the distance-type fuzzy reasoning method appropriately. Consequently, this algorithm is veg simple and extremely fast, requiring almost no learning time. Finally, the effectiveness of this learning algorithm is verified by simulation studies.

• バイオメディカル・ファジィ・システム学会の論文

著者

• Mizumoto M

  Faculty Of Information Science And Technology Osaka Electro-communication University

• Mizumoto Masaharu

  Faculty Of Engineering Science Osaka University

• Wang Shuoyu

  Faculty Of Engineering Kochi University Of Technology

• Tsuchiya Takeshi

  Faculty Of Engineering Hokkaido University

関連論文

• On Reasoning Conditions of Koczy's Interpolative Reasoning
• A Note on Designing Learning Rates in a Class of Neuro-Fuzzy Learning Algorithms
• Tuning Fuzzy Rules Based on an Extended Neuro-Fuzzy Learning Algorithm
• Implementation of a Fuzzy Sets Manipulation System
• A Learning Algorithm for Distance-type Fuzzy Reasoning Method

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