Staff View: Daily pan-evaporation estimation in different agro-climatic zones using novel hybrid support vector regression optimized by Salp swarm algorithm in conjunction with gamma test

Daily pan-evaporation estimation in different agro-climatic zones using novel hybrid support vector regression optimized by Salp swarm algorithm in conjunction with gamma test

Ensuring accurate estimation of evaporation is weighty for effective planning and judicious management of available water resources for agricultural practices. Thus, this work enhances the potential of support vector regression (SVR) optimized with a novel nature-inspired algorithm, namely, Slap Swa...

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Main Authors:	Malik, Anurag, Tikhamarine, Yazid, Al-Ansari, Nadhir, Shahid, Shamsuddin, Sekhon, Harkanwaljot Singh, Pal, Raj Kumar, Rai, Priya, Pandey, Kusum, Singh, Padam, Ahmed Elbeltagi, Ahmed Elbeltagi, Sammen, Saad Shauket
Format:	Article
Published:	Taylor and Francis Ltd. 2021
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://eprints.utm.my/id/eprint/97695/ http://dx.doi.org/10.1080/19942060.2021.1942990
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id	my.utm.97695
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spelling	my.utm.976952022-10-31T01:08:40Z http://eprints.utm.my/id/eprint/97695/ Daily pan-evaporation estimation in different agro-climatic zones using novel hybrid support vector regression optimized by Salp swarm algorithm in conjunction with gamma test Malik, Anurag Tikhamarine, Yazid Al-Ansari, Nadhir Shahid, Shamsuddin Sekhon, Harkanwaljot Singh Pal, Raj Kumar Rai, Priya Pandey, Kusum Singh, Padam Ahmed Elbeltagi, Ahmed Elbeltagi Sammen, Saad Shauket TA Engineering (General). Civil engineering (General) Ensuring accurate estimation of evaporation is weighty for effective planning and judicious management of available water resources for agricultural practices. Thus, this work enhances the potential of support vector regression (SVR) optimized with a novel nature-inspired algorithm, namely, Slap Swarm Algorithm (SVR-SSA) against Whale Optimization Algorithm (SVR-WOA), Multi-Verse Optimizer (SVR-MVO), Spotted Hyena Optimizer (SVR-SHO), Particle Swarm Optimization (SVR-PSO), and Penman model (PM). Daily EP (pan-evaporation) was estimated in two different agro-climatic zones (ACZ) in northern India. The optimal combination of input parameters was extracted by applying the Gamma test (GT). The outcomes of the hybrid of SVR and PM models were equated with recorded daily EP observations based on goodness-of-fit measures along with graphical scrutiny. The results of the appraisal showed that the novel hybrid SVR-SSA-5 model performed superior (MAE = 0.697, 1.556, 0.858 mm/day, RMSE = 1.116, 2.114, 1.202 mm/day, IOS = 0.250, 0.350, 0.303, NSE = 0.0.861, 0.750, 0.834, PCC = 0.929, 0.868, 0.918, IOA = 0.960, 0.925, 0.956) than other models in testing phase at Hisar, Bathinda, and Ludhiana stations, respectively. In conclusion, the hybrid SVR-SSA model was identified as more suitable, robust, and reliable than the other models for daily EP estimation in two different ACZ. Taylor and Francis Ltd. 2021 Article PeerReviewed Malik, Anurag and Tikhamarine, Yazid and Al-Ansari, Nadhir and Shahid, Shamsuddin and Sekhon, Harkanwaljot Singh and Pal, Raj Kumar and Rai, Priya and Pandey, Kusum and Singh, Padam and Ahmed Elbeltagi, Ahmed Elbeltagi and Sammen, Saad Shauket (2021) Daily pan-evaporation estimation in different agro-climatic zones using novel hybrid support vector regression optimized by Salp swarm algorithm in conjunction with gamma test. Engineering Applications of Computational Fluid Mechanics, 15 (1). pp. 1075-1094. ISSN 1994-2060 http://dx.doi.org/10.1080/19942060.2021.1942990 DOI : 10.1080/19942060.2021.1942990
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Malik, Anurag Tikhamarine, Yazid Al-Ansari, Nadhir Shahid, Shamsuddin Sekhon, Harkanwaljot Singh Pal, Raj Kumar Rai, Priya Pandey, Kusum Singh, Padam Ahmed Elbeltagi, Ahmed Elbeltagi Sammen, Saad Shauket Daily pan-evaporation estimation in different agro-climatic zones using novel hybrid support vector regression optimized by Salp swarm algorithm in conjunction with gamma test
description	Ensuring accurate estimation of evaporation is weighty for effective planning and judicious management of available water resources for agricultural practices. Thus, this work enhances the potential of support vector regression (SVR) optimized with a novel nature-inspired algorithm, namely, Slap Swarm Algorithm (SVR-SSA) against Whale Optimization Algorithm (SVR-WOA), Multi-Verse Optimizer (SVR-MVO), Spotted Hyena Optimizer (SVR-SHO), Particle Swarm Optimization (SVR-PSO), and Penman model (PM). Daily EP (pan-evaporation) was estimated in two different agro-climatic zones (ACZ) in northern India. The optimal combination of input parameters was extracted by applying the Gamma test (GT). The outcomes of the hybrid of SVR and PM models were equated with recorded daily EP observations based on goodness-of-fit measures along with graphical scrutiny. The results of the appraisal showed that the novel hybrid SVR-SSA-5 model performed superior (MAE = 0.697, 1.556, 0.858 mm/day, RMSE = 1.116, 2.114, 1.202 mm/day, IOS = 0.250, 0.350, 0.303, NSE = 0.0.861, 0.750, 0.834, PCC = 0.929, 0.868, 0.918, IOA = 0.960, 0.925, 0.956) than other models in testing phase at Hisar, Bathinda, and Ludhiana stations, respectively. In conclusion, the hybrid SVR-SSA model was identified as more suitable, robust, and reliable than the other models for daily EP estimation in two different ACZ.
format	Article
author	Malik, Anurag Tikhamarine, Yazid Al-Ansari, Nadhir Shahid, Shamsuddin Sekhon, Harkanwaljot Singh Pal, Raj Kumar Rai, Priya Pandey, Kusum Singh, Padam Ahmed Elbeltagi, Ahmed Elbeltagi Sammen, Saad Shauket
author_facet	Malik, Anurag Tikhamarine, Yazid Al-Ansari, Nadhir Shahid, Shamsuddin Sekhon, Harkanwaljot Singh Pal, Raj Kumar Rai, Priya Pandey, Kusum Singh, Padam Ahmed Elbeltagi, Ahmed Elbeltagi Sammen, Saad Shauket
author_sort	Malik, Anurag
title	Daily pan-evaporation estimation in different agro-climatic zones using novel hybrid support vector regression optimized by Salp swarm algorithm in conjunction with gamma test
title_short	Daily pan-evaporation estimation in different agro-climatic zones using novel hybrid support vector regression optimized by Salp swarm algorithm in conjunction with gamma test
title_full	Daily pan-evaporation estimation in different agro-climatic zones using novel hybrid support vector regression optimized by Salp swarm algorithm in conjunction with gamma test
title_fullStr	Daily pan-evaporation estimation in different agro-climatic zones using novel hybrid support vector regression optimized by Salp swarm algorithm in conjunction with gamma test
title_full_unstemmed	Daily pan-evaporation estimation in different agro-climatic zones using novel hybrid support vector regression optimized by Salp swarm algorithm in conjunction with gamma test
title_sort	daily pan-evaporation estimation in different agro-climatic zones using novel hybrid support vector regression optimized by salp swarm algorithm in conjunction with gamma test
publisher	Taylor and Francis Ltd.
publishDate	2021
url	http://eprints.utm.my/id/eprint/97695/ http://dx.doi.org/10.1080/19942060.2021.1942990
_version_	1748180495335686144
score	13.211869

Daily pan-evaporation estimation in different agro-climatic zones using novel hybrid support vector regression optimized by Salp swarm algorithm in conjunction with gamma test

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