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|Title:||Real-time flood hydrograph predictions using rating curve and soft computing methods (GA, ANN)||Authors:||Tayfur, Gökmen||Keywords:||Artificial neural network
|Issue Date:||2022||Publisher:||Elsevier||Abstract:||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. © 2023 Elsevier Inc. All rights reserved.||URI:||https://doi.org/10.1016/B978-0-12-821962-1.00019-2
|Appears in Collections:||Civil Engineering / İnşaat Mühendisliği|
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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checked on Dec 4, 2023
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