مقاله شماره ۹: Credit Card Fraud Detection by Combining Neural Network and Grasshopper Optimization Algorithm
With the accelerated development of Internet finance, electronic funds transfer, and the rapid growth of credit card activity, credit cards play a very important role in every area of life today. There are some risks in this regard that are considered serious threats to both issuers and cardholders. The increasing number of fraudulent credit card transactions forged credit cards and fraudulent use of expired credit cards have led to increased losses. Therefore, finding fraud detection techniques accurately and quickly has become an important topic in current investigations. In this study, after normalizing and reducing the dimensionality of the data using the PCA algorithm, we used the modified perceptron neural network and the grasshopper algorithm to classify the data. In this study, we use the grasshopper algorithm to adjust the weights and biases of neural networks. In the end, we were able to achieve 99.20% accuracy.
Grasshopper Optimization Algorithm
Alaa Mahdi Alkhafaji1, Ghassan Fadhil Smaisim*2, Falah mahdi Alobayes3, Monireh Houshmand4
1Faculty of Electrical Department, Imam Reza International University Mashhad, Iran.
2Department of Mechanical Engineering, Faculty of Engineering, University of Kufa, Kufa, Iraq.
3General Direct of electricity distribution for middle Euphrates, Ministry of Electricity, Iraq.
4Faculty of Electrical Department, Imam Reza International University Mashhad, Iran.
دانلود فایل مقاله منابع XML