Character Recognition Using Neural Network Learned by Artificial Bee Algorithm
DOI:
https://doi.org/10.25195/ijci.v41i1.96Keywords:
Neural Network, Artificial Neural Network, Artificial Bee Algorithm, Pattern Recognition, Back Propagation, and Classification field.Abstract
Character Recognition is the text recognition system that allows hard copies of written or printed text to be rendered
into editable, soft copy versions. In this paper, work has been performed to recognize pattern using multilayer perceptron
learning by Artificial Bee algorithm (ABC) that simulates the intelligent foraging behavior of a honey bee swarm. Multilayer
Perceptron (MLP) trained with the standard back propagation (BP) algorithm normally utilizes computationally intensive
training algorithms. One of the crucial problems with the BP algorithm is that it can sometimes yield the networks with
suboptimal weights because of the presence of many local optima in the solutions space. The suggested method is to use ABC for
learn the Neural Networks, to solve text character recognition problem, by update the Neural Networks weights. A comparison
studies are made between ABC and BP methods in NN learning to specify which is better in solving character recognition
problem.
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