In this paper we present the systematic trajectory search algorithm (STSA) which first globally explores the solution space then makes thorough local searches in promising areas. The STSA has been tested on training feedforward neural networks to solve the n-bit parity problem of various sizes and two real medical diagnosis problems. The experimental results show that the feedforward neural networks trained by the proposed algorithm have very good classification ability.

The Systematic Trajectory Search Algorithm for Feedforward Neural Network Training.pdf

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