A Study of Pumping Station Water Level Forecasting and Operation System
Date Issued
2007
Date
2007
Author(s)
Lee, Wong-Shuo
DOI
zh-TW
Abstract
The pumping station is one of the most important facilities in preventing flooding events takes place for the Taipei city. When the water level of the river arises a certain level, we can only rely on the operation of pumping stations to discharge water from the city area to the rivers. The objective of this study include is to construct a forecast model and to investigate the suitability of the operating rule. The first main constructs a BPNN model to predict one-step-ahead and two-step-ahead sewer drainage system of Chung-Kang during flood events and investigate the influence of amplitude or noise data on the model and provide effective solution. The results show that the BPNN can suitably predict multi-step-ahead water level in the sewer system, while the data processing can improve the accuracy of the model. The second part is to investigate the suitability of the existing operating rule lines of the pumping station and comparing the results obtained by simulating a number of adjusted operating rule lines based on historical data sets with the historical information. The results indicate that the operation of the pumping station of Chung-Kang can be improved.
Subjects
下水道系統
倒傳遞類神經網路
資料雜訊處理
抽水機組操作規線
sewer drainage system
Back Propagation Neural Network
data processing
operating rule lines of the pumping station
Type
thesis
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