Artificial bee colony algorithm for modular neural network

Authors:
Chen Zhuo-Ming;Wang Yun-Xia;Ling Wei-Xin;Xing Zhen;Xiao Han-Lin-Wei
Affiliations:
The Centre of Language Disorder, The First Affiliated Hospital, Jinan University, Guangzhou, China;School of Science, South China University of Technology, Guangzhou, China;School of Science, South China University of Technology, Guangzhou, China;School of Science, South China University of Technology, Guangzhou, China;The Centre of Language Disorder, The First Affiliated Hospital, Jinan University, Guangzhou, China
Venue:
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
Year:
2013

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Abstract

The Artificial bee colony (ABC) algorithm is simple, robust and has been used in the optimization of synaptic weights from an Artificial Neural Network (ANN). However, this is not enough to generate a robust ANN. Modular neural networks (MNNs) are especially efficient for certain classes of regression and classification problems, as compared to the conventional monolithic artificial neural networks. In this paper, we present a model of MNN based on ABC algorithm (ABC-MNN). Experiments show that, compared to the monolithic ABC-NN model, classifier designed in this model has higher training accuracy and generalization performance.