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.
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© 2001 Springer-Verlag Berlin Heidelberg
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Tettamanzi, A., Tomassini, M. (2001). Evolutionary Design of Fuzzy Systems. In: Soft Computing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-04335-6_5
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DOI: https://doi.org/10.1007/978-3-662-04335-6_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-07583-4
Online ISBN: 978-3-662-04335-6
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