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

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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.

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Acknowledgements

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

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Authors and Affiliations

  1. Northeastern University, Shenyang, Liaoning, People’s Republic of China

    Lijie Zhang, Jianchang Liu & Shubin Tan

  2. Ningxia Institute of Science and Technology, Shizuishan, Ningxia, People’s Republic of China

    Lijie Zhang

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  1. Lijie Zhang
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Correspondence to Lijie Zhang.

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Zhang, L., Liu, J. & Tan, S. The radial basis function analysis of fire evacuation model based on RBF neural network. Cluster Comput 22 (Suppl 3), 6417–6424 (2019). https://doi.org/10.1007/s10586-018-2159-2

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  • DOI: https://doi.org/10.1007/s10586-018-2159-2

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