Modeling of watershed flood forecasting with time series artificial neural network algorithm

Cho Chung Yang*, Chang Shian Chen, Liang-Cheng Chang

*此作品的通信作者

研究成果: Paper同行評審

1 引文 斯高帕斯(Scopus)

摘要

In order to forecast the flood discharge of downstream gauging station by the artificial neural network (ANN) algorithm efficiently, the linear transfer function method (LTF) and parameter significance T-test are proposed to determine the number of network input elements. In addition, time series ARIMA model for all upstream gauging stations is constructed to offer the forecasting discharges which are input data for watershed ANN flood forecasting model. From the application in Wu-Shi basin, the model verified results of the following one hour through the following three hours flood forecasting are good. One may conclude that the algorithm of time series ANN flood forecasting can simulate the phenomena of flood transportation and forecast the flood discharge of watershed efficiently.

原文American English
頁面903-908
頁數6
出版狀態Published - 1 1月 1998
事件Proceedings of the 1998 International Water Resources Engineering Conference. Part 2 (of 2) - Memphis, TN, USA
持續時間: 3 8月 19987 8月 1998

Conference

ConferenceProceedings of the 1998 International Water Resources Engineering Conference. Part 2 (of 2)
城市Memphis, TN, USA
期間3/08/987/08/98

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