Evolutionary radial basis function networks

Research output: Chapter in Book/Report/Conference proceedingChapter

9 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
PublisherSpringer Verlag
Pages105-139
Number of pages35
DOIs
Publication statusPublished - 1 Jan 2019
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume780
ISSN (Print)1860-949X

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  • Cite this

    Mirjalili, S. (2019). Evolutionary radial basis function networks. In Studies in Computational Intelligence (pp. 105-139). (Studies in Computational Intelligence; Vol. 780). Springer Verlag. https://doi.org/10.1007/978-3-319-93025-1_8