Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering

Enterprise Credit Evaluation Model Based on Genetic Algorithm Optimization BP Neural Network

Authors
Yu-jing Zhang, Qian Li, Zhi-wang Jiang, Hong-xia Zhang
Corresponding Author
Yu-jing Zhang
Available Online April 2015.
DOI
https://doi.org/10.2991/amcce-15.2015.31How to use a DOI?
Keywords
Power supply enterprise; Credit evaluation; Genetic algorithm; BP neural network
Abstract
Credit is very important for the enterprise, analysis of a comprehensive evaluation of enterprise credit, can enhance the risk control ability of enterprise credit, improve enterprise credit rating.The paper establishes BP neural network credit evaluation model based on genetic algorithm GA optimization ,and to the power supply enterprise credit evaluation as an example, to verify the practicability of the model in the evaluation of enterprise credit. Examples of verification results indicate that the genetic algorithm (GA) to optimize the BP neural network is better than traditional BP neural network , it's evaluation has higher accuracy, stronger generalization ability, more suitable for the enterprise credit evaluation. Introduction
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2015 International Conference on Automation, Mechanical Control and Computational Engineering
Part of series
Advances in Intelligent Systems Research
Publication Date
April 2015
ISBN
978-94-62520-64-6
ISSN
1951-6851
DOI
https://doi.org/10.2991/amcce-15.2015.31How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yu-jing Zhang
AU  - Qian Li
AU  - Zhi-wang Jiang
AU  - Hong-xia Zhang
PY  - 2015/04
DA  - 2015/04
TI  - Enterprise Credit Evaluation Model Based on Genetic Algorithm Optimization BP Neural Network
BT  - 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SP  - 174
EP  - 178
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.31
DO  - https://doi.org/10.2991/amcce-15.2015.31
ID  - Zhang2015/04
ER  -