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Data on optimization of the non-linear Muskingum flood routing in Kardeh River using Goa algorithm
This article describes the time series data for optimizing the Non-linear Muskingum flood routing of the Kardeh River, located in Northeastern of Iran for a period of 2 days (from 27 April 1992 to 28 April 1992). The utilized time-series data included river inflow, Storage volume and river outflow....
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083777/ https://www.ncbi.nlm.nih.gov/pubmed/32215307 http://dx.doi.org/10.1016/j.dib.2020.105398 |
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author | Khalifeh, Saeid Esmaili, Kazem Khodashenas, SaeedReza Akbarifard, Saeid |
author_facet | Khalifeh, Saeid Esmaili, Kazem Khodashenas, SaeedReza Akbarifard, Saeid |
author_sort | Khalifeh, Saeid |
collection | PubMed |
description | This article describes the time series data for optimizing the Non-linear Muskingum flood routing of the Kardeh River, located in Northeastern of Iran for a period of 2 days (from 27 April 1992 to 28 April 1992). The utilized time-series data included river inflow, Storage volume and river outflow. In this data article, a model based on the Grasshopper Optimization Algorithm (GOA) was developed for the optimization of the Non-linear Muskingum flood routing model. The GOA algorithm was compared with other metaheuristic algorithms such as the Genetic Algorithm (GA) and Harmony search (HS). The analysis showed that the best solutions achieved by the GOA, Genetic Algorithm (GA), and Harmony search (HS) were 3.53, 5.29, and 5.69, respectively. The analysis of these datasets revealed that the GOA algorithm was superior to GA and HS algorithms for the optimal flood routing river problem. |
format | Online Article Text |
id | pubmed-7083777 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-70837772020-03-25 Data on optimization of the non-linear Muskingum flood routing in Kardeh River using Goa algorithm Khalifeh, Saeid Esmaili, Kazem Khodashenas, SaeedReza Akbarifard, Saeid Data Brief Computer Science This article describes the time series data for optimizing the Non-linear Muskingum flood routing of the Kardeh River, located in Northeastern of Iran for a period of 2 days (from 27 April 1992 to 28 April 1992). The utilized time-series data included river inflow, Storage volume and river outflow. In this data article, a model based on the Grasshopper Optimization Algorithm (GOA) was developed for the optimization of the Non-linear Muskingum flood routing model. The GOA algorithm was compared with other metaheuristic algorithms such as the Genetic Algorithm (GA) and Harmony search (HS). The analysis showed that the best solutions achieved by the GOA, Genetic Algorithm (GA), and Harmony search (HS) were 3.53, 5.29, and 5.69, respectively. The analysis of these datasets revealed that the GOA algorithm was superior to GA and HS algorithms for the optimal flood routing river problem. Elsevier 2020-03-10 /pmc/articles/PMC7083777/ /pubmed/32215307 http://dx.doi.org/10.1016/j.dib.2020.105398 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Computer Science Khalifeh, Saeid Esmaili, Kazem Khodashenas, SaeedReza Akbarifard, Saeid Data on optimization of the non-linear Muskingum flood routing in Kardeh River using Goa algorithm |
title | Data on optimization of the non-linear Muskingum flood routing in Kardeh River using Goa algorithm |
title_full | Data on optimization of the non-linear Muskingum flood routing in Kardeh River using Goa algorithm |
title_fullStr | Data on optimization of the non-linear Muskingum flood routing in Kardeh River using Goa algorithm |
title_full_unstemmed | Data on optimization of the non-linear Muskingum flood routing in Kardeh River using Goa algorithm |
title_short | Data on optimization of the non-linear Muskingum flood routing in Kardeh River using Goa algorithm |
title_sort | data on optimization of the non-linear muskingum flood routing in kardeh river using goa algorithm |
topic | Computer Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083777/ https://www.ncbi.nlm.nih.gov/pubmed/32215307 http://dx.doi.org/10.1016/j.dib.2020.105398 |
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