Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm

Water scarcity is a serious problem throughout the world. One critical part of this problem is supplying sufficient water to meet irrigation demands for agricultural production. The present study introduced an improved weed algorithm for reservoir operation with the aim of decreasing irrigation defi...
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Autor*in:	Mohammad Ehteram [verfasserIn] Vijay P. Singh [verfasserIn] Hojat Karami [verfasserIn] Khosrow Hosseini [verfasserIn] Mojgan Dianatikhah [verfasserIn] Md. Shabbir Hossain [verfasserIn] Chow Ming Fai [verfasserIn] Ahmed El-Shafie [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	water resources management Aswan High Dam weed algorithm irrigation demands

Übergeordnetes Werk:	In: Water - MDPI AG, 2010, 10(2018), 9, p 1267
Übergeordnetes Werk:	volume:10 ; year:2018 ; number:9, p 1267

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/w10091267

Katalog-ID:	DOAJ047878703

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520			\|a Water scarcity is a serious problem throughout the world. One critical part of this problem is supplying sufficient water to meet irrigation demands for agricultural production. The present study introduced an improved weed algorithm for reservoir operation with the aim of decreasing irrigation deficits. The Aswan High Dam, one of the most important dams in Egypt, was selected for this study to supply irrigation demands. The improved weed algorithm (IWA) had developed local search ability so that the exploration ability for the IWA increased and it could escape from local optima. Three inflows (low, medium and high) to the reservoir were considered for the downstream demands. For example, the average solution for the IWA at high inflow was 0.985 while it was 1.037, 1.040, 1.115 and 1.121 for the weed algorithm (WA), bat algorithm (BA), improved particle swarm optimization algorithm (IPSOA) and genetic algorithm (GA). This meant that the IWA decreased the objective function for high inflow by 5.01%, 5.20%, 11.65% and 12% compared to the WA, BA, IPSOA and GA, respectively. The computational time for the IWA at high inflow was 22 s, which was 12%, 18%, 24% and 29% lower than the WA, BA, IPSOA and GA, respectively. Results indicated that the IWA could meet the demands at all three inflows. The reliability index for the IWA for the three inflows was greater than the WA, BA, IPSOA and GA, meaning that the released water based on IWA could well supply the downstream demands. Thus, the improved weed algorithm is suggested for solving complex problems in water resources management.
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language	English
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authorswithroles_txt_mv	Mohammad Ehteram @@aut@@ Vijay P. Singh @@aut@@ Hojat Karami @@aut@@ Khosrow Hosseini @@aut@@ Mojgan Dianatikhah @@aut@@ Md. Shabbir Hossain @@aut@@ Chow Ming Fai @@aut@@ Ahmed El-Shafie @@aut@@
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callnumber-first	T - Technology
author	Mohammad Ehteram
spellingShingle	Mohammad Ehteram misc TC1-978 misc TD201-500 misc water resources management misc Aswan High Dam misc weed algorithm misc irrigation demands misc Hydraulic engineering misc Water supply for domestic and industrial purposes Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm
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topic_title	TC1-978 TD201-500 Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm water resources management Aswan High Dam weed algorithm irrigation demands
topic	misc TC1-978 misc TD201-500 misc water resources management misc Aswan High Dam misc weed algorithm misc irrigation demands misc Hydraulic engineering misc Water supply for domestic and industrial purposes
topic_unstemmed	misc TC1-978 misc TD201-500 misc water resources management misc Aswan High Dam misc weed algorithm misc irrigation demands misc Hydraulic engineering misc Water supply for domestic and industrial purposes
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title	Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm
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title_full	Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm
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author_browse	Mohammad Ehteram Vijay P. Singh Hojat Karami Khosrow Hosseini Mojgan Dianatikhah Md. Shabbir Hossain Chow Ming Fai Ahmed El-Shafie
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title_sort	irrigation management based on reservoir operation with an improved weed algorithm
callnumber	TC1-978
title_auth	Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm
abstract	Water scarcity is a serious problem throughout the world. One critical part of this problem is supplying sufficient water to meet irrigation demands for agricultural production. The present study introduced an improved weed algorithm for reservoir operation with the aim of decreasing irrigation deficits. The Aswan High Dam, one of the most important dams in Egypt, was selected for this study to supply irrigation demands. The improved weed algorithm (IWA) had developed local search ability so that the exploration ability for the IWA increased and it could escape from local optima. Three inflows (low, medium and high) to the reservoir were considered for the downstream demands. For example, the average solution for the IWA at high inflow was 0.985 while it was 1.037, 1.040, 1.115 and 1.121 for the weed algorithm (WA), bat algorithm (BA), improved particle swarm optimization algorithm (IPSOA) and genetic algorithm (GA). This meant that the IWA decreased the objective function for high inflow by 5.01%, 5.20%, 11.65% and 12% compared to the WA, BA, IPSOA and GA, respectively. The computational time for the IWA at high inflow was 22 s, which was 12%, 18%, 24% and 29% lower than the WA, BA, IPSOA and GA, respectively. Results indicated that the IWA could meet the demands at all three inflows. The reliability index for the IWA for the three inflows was greater than the WA, BA, IPSOA and GA, meaning that the released water based on IWA could well supply the downstream demands. Thus, the improved weed algorithm is suggested for solving complex problems in water resources management.
abstractGer	Water scarcity is a serious problem throughout the world. One critical part of this problem is supplying sufficient water to meet irrigation demands for agricultural production. The present study introduced an improved weed algorithm for reservoir operation with the aim of decreasing irrigation deficits. The Aswan High Dam, one of the most important dams in Egypt, was selected for this study to supply irrigation demands. The improved weed algorithm (IWA) had developed local search ability so that the exploration ability for the IWA increased and it could escape from local optima. Three inflows (low, medium and high) to the reservoir were considered for the downstream demands. For example, the average solution for the IWA at high inflow was 0.985 while it was 1.037, 1.040, 1.115 and 1.121 for the weed algorithm (WA), bat algorithm (BA), improved particle swarm optimization algorithm (IPSOA) and genetic algorithm (GA). This meant that the IWA decreased the objective function for high inflow by 5.01%, 5.20%, 11.65% and 12% compared to the WA, BA, IPSOA and GA, respectively. The computational time for the IWA at high inflow was 22 s, which was 12%, 18%, 24% and 29% lower than the WA, BA, IPSOA and GA, respectively. Results indicated that the IWA could meet the demands at all three inflows. The reliability index for the IWA for the three inflows was greater than the WA, BA, IPSOA and GA, meaning that the released water based on IWA could well supply the downstream demands. Thus, the improved weed algorithm is suggested for solving complex problems in water resources management.
abstract_unstemmed	Water scarcity is a serious problem throughout the world. One critical part of this problem is supplying sufficient water to meet irrigation demands for agricultural production. The present study introduced an improved weed algorithm for reservoir operation with the aim of decreasing irrigation deficits. The Aswan High Dam, one of the most important dams in Egypt, was selected for this study to supply irrigation demands. The improved weed algorithm (IWA) had developed local search ability so that the exploration ability for the IWA increased and it could escape from local optima. Three inflows (low, medium and high) to the reservoir were considered for the downstream demands. For example, the average solution for the IWA at high inflow was 0.985 while it was 1.037, 1.040, 1.115 and 1.121 for the weed algorithm (WA), bat algorithm (BA), improved particle swarm optimization algorithm (IPSOA) and genetic algorithm (GA). This meant that the IWA decreased the objective function for high inflow by 5.01%, 5.20%, 11.65% and 12% compared to the WA, BA, IPSOA and GA, respectively. The computational time for the IWA at high inflow was 22 s, which was 12%, 18%, 24% and 29% lower than the WA, BA, IPSOA and GA, respectively. Results indicated that the IWA could meet the demands at all three inflows. The reliability index for the IWA for the three inflows was greater than the WA, BA, IPSOA and GA, meaning that the released water based on IWA could well supply the downstream demands. Thus, the improved weed algorithm is suggested for solving complex problems in water resources management.
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title_short	Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm
url	https://doi.org/10.3390/w10091267 https://doaj.org/article/90ddcf5c724641bca85ac852bda08f45 http://www.mdpi.com/2073-4441/10/9/1267 https://doaj.org/toc/2073-4441
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Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm

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