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Please use this identifier to cite or link to this item: http://hdl.handle.net/11133/1055

Title: 類似気象データを用いたニューラルネットワークによる翌日最大電力需要予測
Other Titles: ルイジ キショウ データ オ モチイタ ニュ-ラル ネットワーク ニヨル ヨクジツ サイダイ デンリョク ジュヨウ ヨソク
Daily Peak Load Forecasting by Artificial Neural Network with Similarity Weather Data
Authors: 後藤, 泰之
雪田, 和人
水野, 勝教
一柳, 勝宏
角田, 典生
GOTO, Yasuyuki
YUKITA, Kazuto
MIZUNO, Katsunori
Issue Date: 31-Mar-1998
Publisher: 愛知工業大学
Abstract: Demand for electric power is greatly influenced by weather conditions such as temperature and humidity, and days of the week. So the demands for electric power under similar weather conditions on the same days of the week are supposed to have similarities between their numerical values. The aim of this presentation is to report the result of the experiment with a prediction of the largest demand for electric power by database making of information from SDP data, sampling the days that weather conditions are similar by Pattern Matching, and learning by Neural Networks.
URI: http://hdl.handle.net/11133/1055
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