Evaluation Research on Emergency Management Capability of College Accidents Based on Improved LM-RBF Neural Network
Ning Cheng, Xiaodong Song
Available Online December 2018.
- 10.2991/febm-18.2018.78How to use a DOI?
- Emergency management capability; RBF neural network; LM error correction algorithm
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.
- © 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 -