Design of RBF Neural Network Based on Improved Canopy-K-means algorithm-Reference-Cited by-同舟云学术

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Design of RBF Neural Network Based on Improved Canopy-K-means algorithm

Published:2020-07-03 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2020 4th High Performance Computing and Cluster Technologies Conference & 2020 3rd International Conference on Big Data and Artificial Intelligence
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Author:

Lijie Jia¹,Wenjing Li¹,Junfei Qiao¹

Affiliation:

1. Beijing Key Laboratory of Computational Intelligence and Intelligent System, College of Electronic and Control Engineering, Beijing University of Technology, Beijing, China

Funder

National Key Research and Development Project

Beijing Natural Science Foundation

Beijing Municipal Education Commission Foundation

The National Natural Science Foundation of China

Publisher

ACM

Reference18 articles.

1. Parameter Estimation of RBF-AR Model Based on the EM-EKF Algorithm[J];Xi Y.;Acta Automatica Sinica,2017

2. A Novel UKF-RBF Method Based on Adaptive Noise Factor for Fault Diagnosis in Pumping Unit

3. 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

4. Combination model based on improved K-means clustering algorithm[J];Yang H.;Control Engineering of China,2013

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