|
Abstract
|
In recent years, artificial intelligence (AI) and machine learning methods have become common in many areas of finance, since these techniques are effective in predicting the financial markets, stocks and institutions. On the other hand, with the development of the global economy in recent decades, credit cards have become more popular in business transactions. In this research, the credit card fraud detection method using particle swarm optimization algorithm and multilayer perceptron neural network with the aim of solving the problems of convergence, network defects and system stability is proposed. In the proposed method in order to optimize the weights of the neural network, first the particle swarm optimization algorithm is used to obtain the optimal initial values and then the multilayer perceptron neural network algorithm is used to minimize the error rate to. Estimates will be performed in the MATLAB environment, and the proposed approach will be expected to minimize the error rate and increase the fraud detection rate.
|