Accuracy Analysis of Data Fraud Detection for Company Transactions Using Two-Layered Feed Forward Neural Network Approach Compared with Random Forest

Aim: To find accuracy of data fraud detection for company transactions using two-layered feed forward Neural Network approaches compared with Random Forest. Materials and methods: Number of groups is 2. Group 1 - Two-layered feed forward Neural Network, and Group 2 - Random Forest. Results: The accu...

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Veröffentlicht in:ECS transactions 2022-04, Vol.107 (1), p.13481-13490
Hauptverfasser: B, Dheeraj Kumar, A, Gayathri
Format: Artikel
Sprache:eng
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Zusammenfassung:Aim: To find accuracy of data fraud detection for company transactions using two-layered feed forward Neural Network approaches compared with Random Forest. Materials and methods: Number of groups is 2. Group 1 - Two-layered feed forward Neural Network, and Group 2 - Random Forest. Results: The accuracy of the innovative feed forward Neural Network method is 83.4% and Random Forest is 85.5%. The accuracy of the Random Forest algorithm appears to be a slight increase. Conclusion: Random Forest algorithm finds the fraud detection appearance to be better accuracy than the feed forward Neural Network.
ISSN:1938-5862
1938-6737
DOI:10.1149/10701.13481ecst