标题：Handwritten Marathi Characters Recognition Using Hybrid Evolutionary Gradient Descent of Distributed Error in Multilayer Feed Forward Neural Networks
期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：9
出版社：S.S. Mishra
摘要：In this paper the performance of feedforward neural network with descent gradient of distributed error and genetic algorithm is evaluated for the recognition of handwritten characters of 'Marathi' script. The performance index for the feedforward multilaye.r neural networks is considered here with distributed instantaneous unknown error i.e. different error for different layers. The genetic algorithm is applied here to make the search process more efficient to determine the optimal weight vector from the population of weights. The genetic algorithm here is applied with distributed error and the fitness functio n for the genetic algorithm is also considered as the mean of square distributed error that is different for each layer. Hence the convergence is obtained only when the minimum of different errors is determined. In this performance evaluation it has been analyzed that the proposed method of descent gradient of distributed error with genetic algorithm commonly known as hybrid distributed evolutionary technique for the multil ayer feed forward neural perform s better in terms of accuracy, epochs and number of optimal solutions for given training set and test pattern sets for the pattern recognition problem
