TY - JOUR ID - 154622 TI - Detection of counterfeit banknotes using genetic fuzzy system JO - Journal of Fuzzy Extension and Applications JA - JFEA LA - en SN - 2783-1442 AU - Dirik, Mahmut AD - Department of Computer Engineering, Sirnak University, Turkey. Y1 - 2022 PY - 2022 VL - 3 IS - 4 SP - 302 EP - 312 KW - ANFIS KW - Counterfeit Banknotes KW - Fuzzy inference system KW - Genetic Fuzzy system KW - Genetic Algorithm DO - 10.22105/jfea.2022.345344.1223 N2 - Due to developments in printing technology, the number of counterfeit banknotes is increasing every year. Finding an effective method to detect counterfeit banknotes is an important task in business. Finding a reliable method to detect counterfeit banknotes is a crucial challenge in the world of economic transactions. Due to technological development, counterfeit banknotes may pass through the counterfeit banknote detection system based on physical and chemical properties undetected. In this study, an intelligent counterfeit banknote detection system based on a Genetic Fuzzy System (GFS) is proposed to detect counterfeit banknotes efficiently. GFS is a hybrid system that uses a network architecture to fine-tune the membership functions of a fuzzy inference system. The learning algorithms Fuzzy Classification, Genetic Fuzzy Classification, ANFIS Classification, and Genetic ANFIS Classification were applied to the dataset in the UCI machine learning repository to detect the authenticity of banknotes. The developed model was evaluated based on Accuracy (ACC), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Error Mean, Error STD, and confusion matrix. The experimental results and statistical analysis showed that the classification performance of the proposed model was evaluated as follows: Fuzzy = 97.64%, GA_Fuzzy = 98.60%, ANFIS = 80.83%, GA_ANFIS = 97.72% accuracy (ACC). This shows the significant potential of the proposed GFS models for fraud detection. UR - https://www.journal-fea.com/article_154622.html L1 - https://www.journal-fea.com/article_154622_1194de5a86b581c9416be7aaf0bcab25.pdf ER -