Evolutionary Design of Fuzzy Systems

Andrea Tettamanzi () and Marco Tomassini ()
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Andrea Tettamanzi: University of Milan, Information Technology Department
Marco Tomassini: University of Lausanne, Computer Science Institute

Chapter Chapter 5 in Soft Computing, 2001, pp 161-199 from Springer

Abstract: Abstract ONE of the reasons for the success of fuzzy logic is that the linguistic variables, values, and rules allow the engineer to seamlessly translate human knowledge into systems that work. What is a strength in some cases, however, is a weakness in others. If expert knowledge is not available, there is no ready made recipe to put together a fuzzy system from scratch, as is the case with more conventional techniques. This is where evolutionary algorithms come into play.

Keywords: Membership Function; Evolutionary Algorithm; Fuzzy System; Fuzzy Controller; Evolutionary Design (search for similar items in EconPapers)
Date: 2001
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DOI: 10.1007/978-3-662-04335-6_5

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