Training Algorithm of BP Networks Based on Improved Ant Colony Algorithm

Abstract:

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This study proposes a new method to search optimal parameters of BP networks based on improved ant colony algorithm. The algorithm proposed that each ant searches only around the best solution of the previous iteration with, which can reduce search space fast. is proposed for improving the solution performance to reach global optimum fairly quickly. Simulation results indicate that optimize parameters of BP networks with this method can not only overcome the limitations both the slow convergence and the local extreme values by basic BP algorithm, but also improve the learning ability and generalization ability.

Info:

Periodical:

Advanced Materials Research (Volumes 204-210)

Edited by:

Helen Zhang, Gang Shen and David Jin

Pages:

310-313

DOI:

10.4028/www.scientific.net/AMR.204-210.310

Citation:

Y. Y. Ren et al., "Training Algorithm of BP Networks Based on Improved Ant Colony Algorithm", Advanced Materials Research, Vols. 204-210, pp. 310-313, 2011

Online since:

February 2011

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Price:

$35.00

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