Research on Evaluation of Enterprise Performance Based on BP Neural Network Improved by Levenberg-marquardt Algorithm

DOI

10.2991/amcce-15.2015.30How to use a DOI?

Keywords

Artificial neural network; BP network; Levenberg-Marquardt algorithm; Performance

Abstract

BP neural network is a multilayer feedforward network for training according to the error back-propagation algorithm , its main advantage is the strong non-linear mapping ability , but the training of BP neural network is easy to fall into local minima, and slow convergence speed. In this paper, through the Levenberg-Marquardt algorithm to improve the BP neural network , using LM algorithm terative results dynamically adjust the convergence direction of neural network,so that each iteration error are decreased, and the convergence speed is fast.Through example analysis, show that the improved BP neural network utility and effectiveness in enterprise performance level evaluation.

Copyright

© 2015, 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/).

Download article (PDF)

TY  - CONF
AU  - Wanyin Du
PY  - 2015/04
DA  - 2015/04
TI  - Research on Evaluation of Enterprise Performance Based on BP Neural Network Improved by Levenberg-marquardt Algorithm
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SP  - 169
EP  - 173
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.30
DO  - 10.2991/amcce-15.2015.30
ID  - Du2015/04
ER  -