چکیده

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.

کلیدواژه:

Fraud Detection

Grasshopper Optimization Algorithm

Neural Network

نویسندگان:

Alaa Mahdi Alkhafaji¹, Ghassan Fadhil Smaisim^*2, Falah mahdi Alobayes³, Monireh Houshmand^4
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.

DOR:

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