Proceedings of the Third International Conference on Economic and Business Management (FEBM 2018)

Evaluation Research on Emergency Management Capability of College Accidents Based on Improved LM-RBF Neural Network

Authors
Ning Cheng, Xiaodong Song
Corresponding Author
Xiaodong Song
Available Online December 2018.
DOI
10.2991/febm-18.2018.78How to use a DOI?
Keywords
Emergency management capability; RBF neural network; LM error correction algorithm
Abstract

College emergency management is an important approach to maintain order and secure safety of campus. For colleges, setting up a scientific and effective evaluation model of emergency management capability is not only an important means to enhance the level of emergency management, but also the key to ensure normal operation of education. This paper proposes an improved RBF artificial neural network algorithm based on LM. This algorithm improves the compact ratio and error convergence speed of RBF neural network, and has better processing ability and higher robustness in the highly nonlinear problem-emergencies.

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 Third International Conference on Economic and Business Management (FEBM 2018)
Series
Advances in Economics, Business and Management Research
Publication Date
December 2018
ISBN
978-94-6252-623-5
ISSN
2352-5428
DOI
10.2991/febm-18.2018.78How 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  - Ning Cheng
AU  - Xiaodong Song
PY  - 2018/12
DA  - 2018/12
TI  - Evaluation Research on Emergency Management Capability of College Accidents Based on Improved LM-RBF Neural Network
BT  - Proceedings of the Third International Conference on Economic and Business Management (FEBM 2018)
PB  - Atlantis Press
SP  - 345
EP  - 348
SN  - 2352-5428
UR  - https://doi.org/10.2991/febm-18.2018.78
DO  - 10.2991/febm-18.2018.78
ID  - Cheng2018/12
ER  -