Forecasting Natural Disasters of Tornados Using mHGN
Résumé
Lots of damages, losses, and costs have been the major concern, why handling natural disasters of tornados is very important. Several attempts using different approaches have been carried out, but up to now the results are not yet satisfactory. More promising approaches through a kind of artificial intelligent forecaster have been started for a while, but the results are still not satisfactory either. The capability of mHGN as a pattern recognizer has opened up a new possibility of recognizing a pattern of tornado many hours earlier. Therefore, it can be used to forecast a tornado more efficiently. The results taken from a simulated circumstances of a multidimensional pattern recognition have shown, that the 91% of accuracy can be regarded as satisfactory. Though, several modifications related to the data representation within the mHGN architecture need to be implemented. The deployment of mHGN in several risky areas of tornados can then be expected as a tool for reducing those damages, losses, and costs.
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