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a multi-layered hidden markov model for real-time fraud detection in electronic financial transactions
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نویسنده
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abukari abdul aziz danaa ,ibrahim mohammed ,abdul-barik alhassan
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منبع
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journal of ai and data mining - 2023 - دوره : 11 - شماره : 4 - صفحه:599 -608
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چکیده
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Hidden markov models (hmms) are machine learning models that has been applied to a range of real-life applications including intrusion detection, pattern recognition, thermodynamics, statistical mechanics among others. a multi-layered hmms for real-time fraud detection and prevention whilst reducing drastically the number of false positives and negatives is proposed and implemented in this study. the study also focused on reducing the parameter optimization and detection times of the proposed models using a hybrid algorithm comprising the baum-welch, genetic and particle-swarm optimization algorithms. simulation results revealed that, in terms of precision, recall and f1-scores, our proposed model performed better when compared to other approaches proposed in literature.
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کلیدواژه
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fraudulent ,hidden markov models ,optimization ,probability ,multi-layered
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آدرس
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tamale technical university, department of computer science, ghana, c. k. tedam university of technology and applied sciences, department of computer science, ghana, university for development studies, department of computer science, ghana
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پست الکترونیکی
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abarik@uds.edu.gh
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Authors
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