Semantic Scholar
Open Access
2016
544 sitasi
Multilayer Perceptron: Architecture Optimization and Training
H. Ramchoun
M. J. Idrissi
Y. Ghanou
M. Ettaouil
Abstrak
— The multilayer perceptron has a large wide of classification and regression applications in many fields: pattern recognition, voice and classification problems. But the architecture choice has a great impact on the convergence of these networks. In the present paper we introduce a new approach to optimize the network architecture, for solving the obtained model we use the genetic algorithm and we train the network with a back-propagation algorithm. The numerical results assess the effectiveness of the theoretical results shown in this paper, and the advantages of the new modeling compared to the previous model in the literature.
Topik & Kata Kunci
Penulis (4)
H
H. Ramchoun
M
M. J. Idrissi
Y
Y. Ghanou
M
M. Ettaouil
Akses Cepat
Informasi Jurnal
- Tahun Terbit
- 2016
- Bahasa
- en
- Total Sitasi
- 544×
- Sumber Database
- Semantic Scholar
- DOI
- 10.9781/ijimai.2016.415
- Akses
- Open Access ✓