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Cluster Computing

, Volume 22, Supplement 3, pp 6417–6424 | Cite as

The radial basis function analysis of fire evacuation model based on RBF neural network

  • Lijie ZhangEmail author
  • Jianchang Liu
  • Shubin Tan
Article
  • 108 Downloads

Abstract

After the occurrence of major accidents, the people in the buildings should be evacuated to safe areas within the shortest time. It is the important part of safe evacuation and reduction of mass mortality accidents. Therefore, the research of fire evacuation problem has highly theoretical and practical values. In the fire evacuation scene, the individual attributes are affected by psychology and behavior among individuals. Based on radial basis function neural network, we used the principal component analysis to determine six main factors affecting evacuation time. These factors are taken as the input of neural network; the evacuation time as the output of neural network. The network was trained by 125 sets of survey data. The quadratic sum error of the model was similar to 0, thus better achieving simulation of actual situation.

Keywords

Fire evacuation Radial basis function Neural network Model establishment 

Notes

Acknowledgements

National Natural Science Foundation of China (NSFC) (Nos. 61374137, 61773106, 61703086), the IAPI Fundamental Research Funds (2013ZCX02-03).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Northeastern UniversityShenyangPeople’s Republic of China
  2. 2.Ningxia Institute of Science and TechnologyShizuishanPeople’s Republic of China

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