NEURAL NETWORKS AND GENETIC ALGORITHM FOR FINGERPRINT PATTERN RECOGNITION

  • Nguyen Quang Hoan Hung Yen University of Technology and Education
  • Nguyen Thi Trang East Asia University of Technology
  • Nguyen Thi Huyen Hung Yen University of Technology and Education
  • Truong Quoc Khanh No. 1 Vocational College Hanoi
  • Nguyen Thi Hoa Vocational College of High Technology Hanoi
Keywords: Backpropagation, Genetic Algorithm, Pattern Fingerprint Recognition, Forecasting

Abstract

In this paper, we integrate Genetic Algorithm (GA) with Backpopagation Neural Network (BPNN to remove local minimums when using Gradient Recent technique for some problems such as pattern recognitions or forecasting. With this method, learning process can be divided in two phases: first phase using GA to define initial NN weighs; second phase using traditional BP Algorithm to receive global optimization weights. We to make some experiments using the intergrated technique on Fingerprint Recognition and to compare the results of the technique with the non-ingterated NN.

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Published
2016-10-11
How to Cite
Nguyen Quang Hoan, Nguyen Thi Trang, Nguyen Thi Huyen, Truong Quoc Khanh, & Nguyen Thi Hoa. (2016). NEURAL NETWORKS AND GENETIC ALGORITHM FOR FINGERPRINT PATTERN RECOGNITION. UTEHY Journal of Applied Science and Technology, 11, 57-62. Retrieved from http://jst.utehy.edu.vn/index.php/jst/article/view/256