Proceedings of the 2018 International Conference on Education Reform and Management Science (ERMS 2018)

Evaluation on Development Capacity of Overseas Chinese Enterprises Based on Improved BP Neural-Networks

Authors
Ke Ma, Xian-shui Sun
Corresponding Author
Ke Ma
Available Online April 2018.
DOI
10.2991/erms-18.2018.91How to use a DOI?
Keywords
Overseas Chinese enterprises, Development capacity, BP neural-networks, Learning algorithm
Abstract

An approach based on improved BP neural-networks is proposed for the evaluation on the development capacity of overseas Chinese enterprise. In order to cope with the slow learning speed and local minimal problems of BP neural-networks, an adaptive learning rate selection method based errors is presented. According to the features of overseas Chinese enterprise, the parameters of input level and number of neurons of hidden level of the BP neural-networks are investigated. Finally, the objective and quantified evaluation result can be achieved from the output neuron.

Copyright
© 2018, 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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Volume Title
Proceedings of the 2018 International Conference on Education Reform and Management Science (ERMS 2018)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
April 2018
ISBN
10.2991/erms-18.2018.91
ISSN
2352-5398
DOI
10.2991/erms-18.2018.91How to use a DOI?
Copyright
© 2018, 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/).

Cite this article

TY  - CONF
AU  - Ke Ma
AU  - Xian-shui Sun
PY  - 2018/04
DA  - 2018/04
TI  - Evaluation on Development Capacity of Overseas Chinese Enterprises Based on Improved BP Neural-Networks
BT  - Proceedings of the 2018 International Conference on Education Reform and Management Science (ERMS 2018)
PB  - Atlantis Press
SP  - 507
EP  - 510
SN  - 2352-5398
UR  - https://doi.org/10.2991/erms-18.2018.91
DO  - 10.2991/erms-18.2018.91
ID  - Ma2018/04
ER  -