Abstract
In this paper, evolution strategy is applied in order to improve the time series prediction accuracy of a Sugeno and Takagi type fuzzy inference system (FIS). The presented approach additionally serves as a method to predetermine the structure of radial basis function networks (RBFN): the number of hidden units as well as the starting parameters for a further optimization are estimated.
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© 1994 Springer-Verlag Berlin Heidelberg
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Wienholt, W. (1994). Improving a Fuzzy Inference System by Means of Evolution Strategy. In: Reusch, B. (eds) Fuzzy Logik. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79386-8_23
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DOI: https://doi.org/10.1007/978-3-642-79386-8_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-58649-4
Online ISBN: 978-3-642-79386-8
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