預測颱風之水庫濁度-以石門水庫為例

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Title:	預測颱風之水庫濁度-以石門水庫為例
Authors:	陳莉 Chen, Li
Contributors:	土木工程學系 Civil Engineering
Keywords:	類神經;濁度預測;時間序列 Neural Network;Predict the Turbidity;time-series
Date:	2006
Issue Date:	2014-06-26 20:44:57 (UTC+8)
Abstract:	每年自5 月份起，即開始進入洪汛期，期間可能因颱風來襲降雨量暴增可能導致石門水庫原水濁度驟增，造成嚴重的停水事件，濁度成為重要課題，故本研究採用類神經網路以及ARIMA 模式對於石門水庫以及下游進水廠進行濁度預測比較，以石門水庫上游雨量站推估石門水庫大壩可能濁度最大發生時間，使用ARIMA 預測下游淨水場之濁度值，作為爾後提升水資源運用及緊急時應變調度之參考。 Every monsoon from May, the typhoon may bring high turbidity in Shih-Men Reservoir to cause the serious shortage of water supply. This study presents the artificial neural networks (ANNs) and ARIMA model to predict the turbidity in Shih-Men Reservoir and
Appears in Collections:	[Department of Civil Engineering] Seminar Papers

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