Interval Type 2 Neuro-Fuzzy Systems Based on Interval Consequents
作者： Janusz Starczewski , Leszek Rutkowski
DOI: 10.1007/978-3-7908-1902-1_87
关键词:
摘要: There are several ways to synthesize fuzzy systems and neural networks. The so-called neuro-fuzzy exhibit advantages of both techniques, namely learning abilities networks natural language description systems. Recently the concept type 2 sets, i.e. sets with membership grades, was introduced inference This paper presents a new system derived under assumption that rule antecedents characterized by interval grades consequents intervals. An application for checking driver’s steering behaviors is given as an example.
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