Optimal Structure and Parameters of BP Neural Network for Curve Fitting Problem

DOI

10.2991/emim-16.2016.334How to use a DOI?

Keywords

BP neural network; Optimal structure and parameters; Curve fitting; Learning rate; Momentum

Abstract

BP neural network is wildly used because of its strong nonlinear processing ability, self-learning capability, fault tolerance capability. Therefore, the structure and parameters of artificial neural network determine the performance of neural networks. The performance of a BP neural network is not only affected by the network structure, but also affected by its parameters. In this article we will discuss the learning rate and momentum parameters matching relationship and its impact on network performance. The experimental results show that for the curve fitting problem there will be an optimal structure and parameters for the BP neural network.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hongjie Yi
AU  - Guangrong Ji
AU  - Jinghua Liu
AU  - Lin Jia
PY  - 2016/04
DA  - 2016/04
TI  - Optimal Structure and Parameters of BP Neural Network for Curve Fitting Problem
BT  - Proceedings of the 6th International Conference on Electronic, Mechanical, Information and Management Society
PB  - Atlantis Press
SP  - 1647
EP  - 1652
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-16.2016.334
DO  - 10.2991/emim-16.2016.334
ID  - Yi2016/04
ER  -