Abstract
AbstractThe 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.KeywordsModular Neural NetworkArtificial Bee Colony AlgorithmLearning Algorithm
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