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Publication Detail
Applications of spatio-temporal forecasting to forest fire prevention
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Journal Article
  • Authors:
    Wang JQ, Cheng T
  • Publication date:
  • Journal:
    Zhongshan Daxue Xuebao/Acta Scientiarum Natralium Universitatis Sunyatseni
  • Volume:
  • Issue:
  • Status:
  • Print ISSN:
A stochastic time series model was constructed to capture the temporal characteristics of each spatially independent subcomponent. Then a dynamic recurrent neural network (DRNN) was built to discover the hidden spatial correlation. Finally, the previous individual temporal and spatial forecasts were combined based upon statistical regression to product the final forecasting result. The results indicated that the forest fire could be forecasted exactly and effectively by the proposed method. Detailed discussions on the performance and the training precision of the model were presented, and the feasibility of forest fire forecasting was analyzed. ISTIFF had comprehensive application value in the forecast of forest fire.
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