Proceedings of The First International Symposium on Management and Social Sciences (ISMSS 2019)

Research on Railway Logistics Resources Optimization Theory

Authors
Chengxia Dai, Zhifeng Zhao
Corresponding Author
Chengxia Dai
Available Online April 2019.
DOI
10.2991/ismss-19.2019.2How to use a DOI?
Keywords
Railway logistics system; integration optimization; BP neural network algorithm; application
Abstract

In the increasingly competitive logistics market, it is very important to scientifically, effectively and objectively evaluate the validity of integration optimization of the railway logistics resources and the core of logistics enterprises. Supported by the multidisciplinary theory, based on the method combined with theory and practice, this paper uses BP neural network algorithm to conduct empirical analysis of the core capability of China’s railway logistics enterprises, and uses AHP method to prove the accuracy of results and obtain a conclusion that the core competition of China’s railway is increasingly enhanced, thus providing a theoretical and practical reference for the development of China’s railway logistics.

Copyright
© 2019, 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 First International Symposium on Management and Social Sciences (ISMSS 2019)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
April 2019
ISBN
978-94-6252-697-6
ISSN
2352-5398
DOI
10.2991/ismss-19.2019.2How to use a DOI?
Copyright
© 2019, 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  - Chengxia Dai
AU  - Zhifeng Zhao
PY  - 2019/04
DA  - 2019/04
TI  - Research on Railway Logistics Resources Optimization Theory
BT  - Proceedings of The First International Symposium on Management and Social Sciences (ISMSS 2019)
PB  - Atlantis Press
SP  - 6
EP  - 11
SN  - 2352-5398
UR  - https://doi.org/10.2991/ismss-19.2019.2
DO  - 10.2991/ismss-19.2019.2
ID  - Dai2019/04
ER  -