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Evolutionary Radial Basis Function Networks

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Evolutionary Algorithms and Neural Networks

Part of the book series: Studies in Computational Intelligence ((SCI,volume 780))

Abstract

Radial Basis Function (RBF) networks are one of the most popular and applied type of neural networks. RBF networks are universal approximators and considered as special form of multilayer feedforward neural networks that contain only one hidden layer with Gaussian based activation functions. This chapter trains such NNs with several optimisation algorithms and compares their performance.

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Authors and Affiliations

  1. Institute for Integrated and Intelligent Systems, Griffith University, Brisbane, QLD, Australia

    Seyedali Mirjalili

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  1. Seyedali Mirjalili
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Correspondence to Seyedali Mirjalili .

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Mirjalili, S. (2019). Evolutionary Radial Basis Function Networks. In: Evolutionary Algorithms and Neural Networks. Studies in Computational Intelligence, vol 780. Springer, Cham. https://doi.org/10.1007/978-3-319-93025-1_8

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