著者
織田 慎一郎 見目 喜重 中川 重康 榊原 建樹
出版者
一般社団法人 電気学会
雑誌
電気学会論文誌. B (ISSN:03854213)
巻号頁・発行日
vol.117, no.8, pp.1146-1151, 1997
被引用文献数
1

So far a single-stage neural network has been proposed to forecast insolation of next day. In the present paper, a multi-stage neural network is developed to reduce forecasting error further. A first-stage neural network forecasts average atmospheric pressure of next day from atmospheric pressure data of previous day. A second-stage neural network forecasts insolation level of next day from the average atmospheric pressure and weather data of previous day. A third-stage neural network forecasts insolation of next day form the insolation level and weather data of previous day. Meteorological data of Omaezaki, Shizuoka at April 1994 are chosen as input data. The insolation values forecasted by the multi-stage and the single-stage neural networks are compared with the measurement ones. The results show that the forecasting error is reduced to 24% (by the multi-stage) from 33% (by the single-stage).

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ひとまず ・予測日射量(ゲットできたら) ・予報気温 ・予報気圧 (・予報(絶対)湿度:いるかな…?) ぐらいを変数にして発電量の推定できないかなぁ? どうも気圧はそれなりにいい変数になり得そうというのはこの辺を見ていて思ったところ。 https://t.co/EGxVCopSXF

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