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Hybrid neuro-genetic based method for solving ill-posed inverse problem occurring in synthesis of electromagnetic fields

机译:基于混合神经遗传学的解决电磁场合成中不适定逆问题的方法

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摘要

Fredholm Integral Equation of the First Kind (FIEFK) is an example of ill-posed problems. Solving this type of equation using conventional methods of dis cretization often leads to an ill-conditioned system of linear equations. This paper deals with the numerical solution for the FIEFK occurring in the synthesis of the electromagnetic fields. To tackle this problem, we propose a hybrid method based on Genetic Algorithms (GAs) and Artificial Neural Networks. The method consists of two major steps. The first step is to find an initial solution by utilizing a GA, and the second is to refine the solution using a regularized neural network. Experimental results prove the efficiency of our proposed method in comparison with a previous work.
机译:第一类Fredholm积分方程(FIEFK)是不适定问题的一个示例。使用传统的离散化方法求解这类方程式通常会导致线性方程组的病态系统。本文研究了在电磁场合成中出现的FIEFK的数值解。为了解决这个问题,我们提出了一种基于遗传算法和人工神经网络的混合方法。该方法包括两个主要步骤。第一步是通过遗传算法找到初始解,第二步是使用正则化神经网络优化解。实验结果证明了我们提出的方法与以前的工作相比的有效性。

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