Detection of copyright banknotes using genetic fuzzy system

Detection of copyright banknotes using genetic fuzzy system

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Due to developments in printing technology, the number of copyright banknotes is increasing every year.Finding an effective method to detect copyright banknotes is an important task in business.Finding a reliable method to detect copyright banknotes is a crucial challenge in veuve ambal rose the world of economic transactions.Due to technological development, copyright banknotes may pass through the copyright banknote detection system based on physical and chemical properties undetected.In this study, an intelligent copyright banknote detection system based on a Genetic Fuzzy System (GFS) is proposed to detect copyright 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 here = 80.83%, GA_ANFIS = 97.72% accuracy (ACC).This shows the significant potential of the proposed GFS models for fraud detection.