Multilayer perceptrons and radial basis function neural network methods for the solution of differential equations: A survey

Multilayer perceptrons and radial basis function neural network methods for the solution of differential equations: A survey

0.00 Avg rating0 Votes
Article ID: iaor201110673
Volume: 62
Issue: 10
Start Page Number: 3796
End Page Number: 3811
Publication Date: Nov 2011
Journal: Computers and Mathematics with Applications
Authors: ,
Keywords: heuristics
Abstract:

Since neural networks have universal approximation capabilities, therefore it is possible to postulate them as solutions for given differential equations that define unsupervised errors. In this paper, we present a wide survey and classification of different Multilayer Perceptron (MLP) and Radial Basis Function (RBF) neural network techniques, which are used for solving differential equations of various kinds. Our main purpose is to provide a synthesis of the published research works in this area and stimulate further research interest and effort in the identified topics. Here, we describe the crux of various research articles published by numerous researchers, mostly within the last 10 years to get a better knowledge about the present scenario.

Reviews

Required fields are marked *. Your email address will not be published.