On artificial neural networks approach with new cost functions

Jafarian A., Measoomy Nia S., Khalili Golmankhaneh A., Baleanu D.

Applied Mathematics and Computation, cilt.339, ss.546-555, 2018 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 339
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1016/j.amc.2018.07.053
  • Dergi Adı: Applied Mathematics and Computation
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.546-555
  • Anahtar Kelimeler: Artificial neural networks approach, Fractional order ordinary differential equation, Least mean squares cost function, Supervised back-propagation learning algorithm
  • Van Yüzüncü Yıl Üniversitesi Adresli: Evet

Özet

In this manuscript, the artificial neural networks approach involving generalized sigmoid function as a cost function, and three-layered feed-forward architecture is considered as an iterative scheme for solving linear fractional order ordinary differential equations. The supervised back-propagation type learning algorithm based on the gradient descent method, is able to approximate this a problem on a given arbitrary interval to any desired degree of accuracy. To be more precise, some test problems are also given with the comparison to the simulation and numerical results given by another usual method.