过程线
额定值曲线
大洪水
计算机科学
人工神经网络
布线(电子设计自动化)
水文学(农业)
数据挖掘
人工智能
工程类
地质学
地理
岩土工程
地貌学
考古
沉积物
计算机网络
出处
期刊:Elsevier eBooks
[Elsevier]
日期:2023-01-01
卷期号:: 325-338
标识
DOI:10.1016/b978-0-12-821962-1.00019-2
摘要
This chapter introduces hydraulic and hydrologic flood routing methods in natural channels. It details hydrological flood routing methods of the Rating Curve and Muskingum. Based on the rating curve method (RCM), it presents real-time flood hydrograph predictions using the genetic algorithm (GA-based RCM) model. In addition, it presents how to make real-time flood hydrograph predictions using the artificial neural network (ANN). The chapter briefly introduces the basics of GA and details how to calibrate and validate the GA-based RCM model using measured real-time flood hydrographs. Similarly, after giving the basics of ANN, it shows how to train and test the ANN model using measured hydrographs. Real hydrograph simulations by the RCM, GA-based RCM, and ANN are presented, and merits of each model are discussed.
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