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Optimization of a modular neural network for pattern recognition using parallel genetic algorithm

Cárdenas M., Melin P., Cruz L.

Journal of Automation Mobile Robotics and Intelligent Systems

2011

Vol. 5, No. 1

77-84

In this paper, the implementation of a Parallel Genetic Algorithm (PGA) for the training stage, and the optimi zation of a monolithic and modular neural network, for pattern recognition are presented. The optimization con sists in obtaining the best architecture in layers, and neu rons per layer achieving the less training error in a shor ter time. The implementation was performed in a multicore architecture, using parallel programming techniques to exploit its resources. We present the results obtained in terms of performance by comparing results of the training stage for sequential and parallel implementations.