Design of K-means clustering-based polynomial radial basis function neural networks (pRBF NNs) realized with the aid of particle swarm optimization and differential evolution

Sung‐Kwun Oh; Wook-Dong Kim; Witold Pedrycz; Su-Chong Joo

doi:10.1016/j.neucom.2011.06.031

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Design of K-means clustering-based polynomial radial basis function neural networks (pRBF NNs) realized with the aid of particle swarm optimization and differential evolution — Sung‐Kwun Oh (2011) | RDL Network

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Design of K-means clustering-based polynomial radial basis function neural networks (pRBF NNs) realized with the aid of particle swarm optimization and differential evolution

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Witold Pedrycz

University of Alberta

Design of K-means clustering-based polynomial radial basis function neural networks (pRBF NNs) realized with the aid of particle swarm optimization and differential evolution

Article 2011 en

Authors

SO
Sung‐Kwun Oh
WK
Wook-Dong Kim
Witold Pedrycz
University of Alberta

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Publication Info

DOI: 10.1016/j.neucom.2011.06.031
Year: 2011
Published: —
Language: en

Article Details

Volume: 78
Issue: 1
Link Of The Paper: https://doi.org/10.1016/j.neucom.2011.06.031

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Created:June 19, 2026

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