An Artificial Neural Network algorithm to solve third-order Emden-Fowler type problems
Publish place: The Second National Conference on Meta-Heuristic Algorithms and Their Applications in Engineering and Science
Publish Year: 1396
نوع سند: مقاله کنفرانسی
زبان: English
View: 555
- Certificate
- من نویسنده این مقاله هستم
این Paper در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
MHAA02_003
تاریخ نمایه سازی: 4 مهر 1396
Abstract:
In this article we suggest, the hybrid algorithm based on Bessel polynomials and Artificial Neural Network (BeNN) to solve non-linear Emden-Fowler type of differential equations.The problems with singular point at x=0 which have the second order of initial values, are modeled in mathematical physics and astrophysics. An unsupervised learning algorithm for a single layer Feed-Forward Neural Network model is proposed. The error back propagation is applied for updating the network parameters and minimizing the error functions. The hidden layer is eliminated by utilizing a series expansion of Bessel polynomials. The obtained outcomes demonstrate that the present methodology is applicable and reliable
Keywords:
Bessel artificial Neural Network , Emden–Fowler equation , Bessel polynomials , Error back Propagation method , Feed-forward Neural Network
Authors
Kourosh Parand
Department of Computer Sciences, Shahid Beheshti University, G.C., Tehran, Iran. Department of Cognitive Modelling, Institute for Cognitive and Brain Sciences,Shahid Beheshti University, G.C., Tehran, Iran
Amin Ghaderi
Department of Computer Sciences, Shahid Beheshti University, G.C., Tehran, Iran