Design Feed Forward Neural network for solving two dimension singularly perturbed integro-differential and integral equation
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Abstract
Recently, there has been an increasing interest in the study of singular and perturbed systems. In this paper design fast feed forward neural network to present a method to solve two dimensions singularly perturbed integro-differential and integral equations. Using a multi-layer having one hidden layer with 7 hidden units (neurons) and one linear output unit the sigmoid activation of each unit is radial basis function and Levenberg – Marquardt (trainlm) training algorithm. Finally the results of numerical experiments are compared with the exact solution in illustrative examples to confirm the accuracy and efficiency of the presented scheme.
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