• DocumentCode
    2918378
  • Title

    The Economic Loss Evaluation of Earthquake Disaster and Simulation Verification Model Based on the Neural Network

  • Author

    Chen, Biao ; Zhang, Jinggao ; Lv, Jun ; Li, Jian

  • Author_Institution
    Sch. of Econ. & Manage., China Univ. of Geosci., Wuhan, China
  • Volume
    3
  • fYear
    2009
  • fDate
    21-22 Nov. 2009
  • Firstpage
    168
  • Lastpage
    171
  • Abstract
    The evaluation and estimate of the loss and damage in earthquake disaster is an important factor for earthquake emergence and post-earthquake reconstruction decision-making. The article firstly selected the evaluation index for the economic loss of earthquake disaster by the method of factor analysis; then established the evaluation model of economic loss in earthquake disaster based on neural network, and performed training to the data collected and the network; finally forecasted the economic loss in earthquake by the trained network, comparing and testing the results of regression analysis. The testing result indicated that the model has a preferable feasibility and practicability.
  • Keywords
    disasters; earthquakes; environmental economics; neural nets; regression analysis; damage estimation; earthquake disaster; earthquake emergence; economic loss evaluation; evaluation index; factor analysis; neural network; postearthquake reconstruction decision-making; regression analysis; simulation verification model; Algorithm design and analysis; Artificial neural networks; Biological neural networks; Biological system modeling; Earthquakes; Economic forecasting; Intelligent networks; Neural networks; Nonlinear systems; Testing; earthquake disaster; economic loss; evaluation; neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
  • Conference_Location
    Nanchang
  • Print_ISBN
    978-0-7695-3859-4
  • Type

    conf

  • DOI
    10.1109/IITA.2009.42
  • Filename
    5369488