General Regression Neural Network Optimization for Handwritten Persian Digits recognition Using Particle Swarm Optimization
Year: 2016
Journal of Information and Computing Science, Vol. 11 (2016), Iss. 2 : pp. 129–135
Abstract
In this paper an optimization algorithm based on Particle Swarm Optimization algorithm is used for handwritten Persian digits recognition with General Regression Neural Network .The system uses image zoning for the digit recognition. General Regression Neural Network accuracy depends on the centers and widths of the hidden layer neuron basis functions (neuron spread). In this paper we use Particle Swarm Optimization algorithm to determine General Regression Neural Network hidden layer spread. Results show that the optimized General Regression Neural Network provides higher recognition ability compared with that of unoptimized General Regression Neural Network.
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2024-JICS-22521
Journal of Information and Computing Science, Vol. 11 (2016), Iss. 2 : pp. 129–135
Published online: 2016-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 7