Volume 8 Number 9 ( Sep. 2013)
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JSW 2013 Vol.8(9): 2231-2237 ISSN: 1796-217X
doi: 10.4304/jsw.8.9.2231-2237

Harmony Search Algorithm with Chaos for Training RBFNN

Jiaqi Di1, 2, Nihong Wang1
1College of information and Computer Engineering, Northeast Forestry University
2College of computer science and information engineering, Harbin Normal University

Abstract—Harmony search algorithm is a heuristic optimization method inspired from the improvisation process of musicians. A new version of harmony search algorithm with chaos is proposed. This algorithm initializes and updates the harmony memory with the chaos optimization algorithm based on secondary carrier wave, adjusts the parameters dynamically to improve the convergence rate and optimization accuracy. In this paper this new algorithm is used to train RBF neural network. The training performance and generalization capability of the new algorithm are tested and verified on function approximation and Iris classification problem. The training time, MSE and accuracies of the new algorithm are compared with standard HS, IHS, GHS algorithms. It turns out that the new algorithm has better convergence rate and accuracy than others. Finally, we applied the new algorithm into the sewage treatment water quality prediction. The relative errors between the actual values and predictive values prove that a RBFNN trained by the new algorithm has better performance than others.

Index Terms—Harmony Search Algorithm, Chaos Optimization Algorithm, RBF Neural Network, Water Quality Prediction.

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Cite: Jiaqi Di, Nihong Wang, "Harmony Search Algorithm with Chaos for Training RBFNN," Journal of Software vol. 8, no. 9, pp. 2231-2237, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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