Automatic Calibration of an Unsteady River Flow Model by Using Dynamically Dimensioned Search Algorithm

Dynamically dimensioned search (DDS) algorithm is a new-type heuristic algorithm which was originally developed by Tolson and Shoemaker in 2007. In this study, the DDS algorithm is applied to automate the calibration process of an unsteady river flow model in the Tamsui River basin, which was develo...

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Main Authors: Fu-Ru Lin, Nan-Jing Wu, Chen-Hao Tu, Ting-Kuei Tsay
Format: Article
Language:English
Published: Hindawi Limited 2017-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2017/7919324
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spelling doaj-90fa1f73d0ba4dc6ab19d0663f7204662020-11-24T23:53:00ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472017-01-01201710.1155/2017/79193247919324Automatic Calibration of an Unsteady River Flow Model by Using Dynamically Dimensioned Search AlgorithmFu-Ru Lin0Nan-Jing Wu1Chen-Hao Tu2Ting-Kuei Tsay3Department of Civil Engineering, National Taiwan University, Taipei City 10617, TaiwanDepartment of Civil and Water Resources Engineering, National Chiayi University, Chiayi City 60004, TaiwanMWH Americas Incorporated, Taiwan Branch, Taipei City 10549, TaiwanDepartment of Civil Engineering, National Taiwan University, Taipei City 10617, TaiwanDynamically dimensioned search (DDS) algorithm is a new-type heuristic algorithm which was originally developed by Tolson and Shoemaker in 2007. In this study, the DDS algorithm is applied to automate the calibration process of an unsteady river flow model in the Tamsui River basin, which was developed by Wu et al. (2007). Data observed during 2012 and 2013 are collected in this study. They are divided into three groups, one for the test case, one for calibration, and one for the validation. To prove that the DDS algorithm is capable of solving this research problem and the convergence property, a test simulation is first performed. In the studied area, the whole river systems are divided into 20 reaches, and each reach has two parameters (nd and nu) to be determined. These two parameters represent resistance coefficients for low- and high-water conditions. Comparing with another algorithm, it is shown that the DDS algorithm has not only improved on the efficiency but also increased the stability of calibrated results.http://dx.doi.org/10.1155/2017/7919324
collection DOAJ
language English
format Article
sources DOAJ
author Fu-Ru Lin
Nan-Jing Wu
Chen-Hao Tu
Ting-Kuei Tsay
spellingShingle Fu-Ru Lin
Nan-Jing Wu
Chen-Hao Tu
Ting-Kuei Tsay
Automatic Calibration of an Unsteady River Flow Model by Using Dynamically Dimensioned Search Algorithm
Mathematical Problems in Engineering
author_facet Fu-Ru Lin
Nan-Jing Wu
Chen-Hao Tu
Ting-Kuei Tsay
author_sort Fu-Ru Lin
title Automatic Calibration of an Unsteady River Flow Model by Using Dynamically Dimensioned Search Algorithm
title_short Automatic Calibration of an Unsteady River Flow Model by Using Dynamically Dimensioned Search Algorithm
title_full Automatic Calibration of an Unsteady River Flow Model by Using Dynamically Dimensioned Search Algorithm
title_fullStr Automatic Calibration of an Unsteady River Flow Model by Using Dynamically Dimensioned Search Algorithm
title_full_unstemmed Automatic Calibration of an Unsteady River Flow Model by Using Dynamically Dimensioned Search Algorithm
title_sort automatic calibration of an unsteady river flow model by using dynamically dimensioned search algorithm
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2017-01-01
description Dynamically dimensioned search (DDS) algorithm is a new-type heuristic algorithm which was originally developed by Tolson and Shoemaker in 2007. In this study, the DDS algorithm is applied to automate the calibration process of an unsteady river flow model in the Tamsui River basin, which was developed by Wu et al. (2007). Data observed during 2012 and 2013 are collected in this study. They are divided into three groups, one for the test case, one for calibration, and one for the validation. To prove that the DDS algorithm is capable of solving this research problem and the convergence property, a test simulation is first performed. In the studied area, the whole river systems are divided into 20 reaches, and each reach has two parameters (nd and nu) to be determined. These two parameters represent resistance coefficients for low- and high-water conditions. Comparing with another algorithm, it is shown that the DDS algorithm has not only improved on the efficiency but also increased the stability of calibrated results.
url http://dx.doi.org/10.1155/2017/7919324
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