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http://dx.doi.org/10.5351/KJAS.2009.22.1.221

Statistical Modeling on Weather Parameters to Develop Forest Fire Forecasting System  

Trivedi, Manish (Dept of Applied Mathematics, Birla Institute of Technology)
Kumar, Manoj (Dept. of Applied Mathematics, Birla Institute of Technology)
Shukla, Ripunjai (Dept. of Applied Mathematics, Birla Institute of Technology)
Publication Information
The Korean Journal of Applied Statistics / v.22, no.1, 2009 , pp. 221-235 More about this Journal
Abstract
This manuscript illustrates the comparative study between ARIMA and Exponential Smoothing modeling to develop forest fire forecasting system using different weather parameters. In this paper, authors have developed the most suitable and closest forecasting models like ARIMA and Exponential Smoothing techniques using different weather parameters. Authors have considered the extremes of the Wind speed, Radiation, Maximum Temperature and Deviation Temperature of the Summer Season form March to June month for the Ranchi Region in Jharkhand. The data is taken by own resource with the help of Automatic Weather Station. This paper consists a deep study of the effect of extreme values of the different parameters on the weather fluctuations which creates forest fires in the region. In this paper, the numerical illustration has been incorporated to support the present study. Comparative study of different suitable models also incorporated and best fitted model has been tested for these parameters.
Keywords
ARIMA; Exponential Smoothing; temperature; maximum; minimum; wind speed; radiation;
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