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Learning method of a Neural Network using Genetic Algorithm for 3 Bit Parity Discrimination  

Choi, Jae-Seung (Department of Electronics Engineering, Silla University)
Kim, Chung-Hwa (Division of Electronics Engineering, Chosun University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.44, no.2, 2007 , pp. 11-18 More about this Journal
Abstract
Back propagation algorithm based on a gradient-decent method has been widely used to the training of a neural network. However, this algorithm have some problems such as dropping the minimum value in a local area according to an initial value and setting the number of units in a hidden layer when training the neural network. Accordingly, to solve the above-mentioned problems, this paper proposes a genetic algorithm using the training method of the neural network. Thus, the improved genetic algorithm using a new crossover and mutation method is proposed to discriminate 3 bit parity. Experiments confirm that the proposed system is effective for training speed after demonstrating for generation gap, the number of units in the hidden layer, and the number of individuals.
Keywords
Genetic algorithm; neural network; back propagation algorithm; parity discrimination; the number of units in a hidden layer;
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