二次多項式モデルとNNによる鹿児島県各地区ごとの電力系統台風被害予測について  [in Japanese] ON PREDICTION OF ELECTRIC POWER DAMAGE BY TYPHOONS IN EACH DISTRICT IN KAGOSHIMA PREFECTURE VIA A SECOND-ORDER POLYNOMIAL MODEL AND NN  [in Japanese]

Kagoshima Prefecture has suffered from natural disasters by typhoons repeatedly. They hit power systems very badly and sometimes cut off electricity. To ensure the rapid restoration of electricity supply, one needs to predict the amount of damage by typhoon accurately. This paper considers the damage prediction in each district in Kagoshima Prefecture by using the GA (Genetic Algorithm), a polynomial regression model, and NN (Neural Networks). The track of typhoon is given a special value in each difffent region from Gaussian function made by the GA. A predictor consists of the second-order polynomial regressor at the first stage and the NN at the second stage. This method enables us to predict the number of damaged distribution poles and lines from weather forecasts of typhoon. Effectiveness of the method is assured by applying it to the actual date.

Kagoshima Prefecture has suffered from natural disasters by typhoons repeatedly. They hit power systems very badly and sometimes cut off electricity. To ensure the rapid restoration of electricity supply, one needs to predict the amount of damage by typhoon accurately. This paper considers the damage prediction in each district in Kagoshima Prefecture by using the GA (Genetic Algorithm), a polynomial regression model, and NN (Neural Networks). The track of typhoon is given a special value in each difffent region from Gaussian function made by the GA. A predictor consists of the second-order polynomial regressor at the first stage and the NN at the second stage. This method enables us to predict the number of damaged distribution poles and lines from weather forecasts of typhoon. Effectiveness of the method is assured by applying it to the actual date.