Abstract
In this article we propose the adaptive learning algorithm of neural network with respect to a rapid temperature change of forecasted day. The proposed adaptive learning algorithm is used to shift the learning range of previous year of forecasted day. Therefore, the proposed neural network can be trained by using learning data, including the maximum temperature to be forecasted. The suitability of the proposed approach is illustrated through an application to actual load data of Okinawa Electric Power Company in Japan.