Zobrazeno 1 - 10 of 18 pro vyhledávání: '"Yazid Tikhamarine"'
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Akademický článek
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
Autor: Anurag Malik, Yazid Tikhamarine, Nadhir Al-Ansari, Shamsuddin Shahid, Harkanwaljot Singh Sekhon, Raj Kumar Pal, Priya Rai, Kusum Pandey, Padam Singh, Ahmed Elbeltagi, Saad Shauket Sammen
Publikováno v: Engineering Applications of Computational Fluid Mechanics, Vol 15, Iss 1, Pp 1075-1094 (2021)
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
Externí odkaz: https://doaj.org/article/6d749c4fa6454fdaa690cbab24b98afb
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2
Akademický článek
Enhanced Artificial Neural Network with Harris Hawks Optimization for Predicting Scour Depth Downstream of Ski-Jump Spillway
Autor: Saad Sh. Sammen, Mohammad Ali Ghorbani, Anurag Malik, Yazid Tikhamarine, Mohammad AmirRahmani, Nadhir Al-Ansari, Kwok-Wing Chau
Publikováno v: Applied Sciences, Vol 10, Iss 15, p 5160 (2020)
A spillway is a structure used to regulate the discharge flowing from hydraulic structures such as a dam. It also helps to dissipate the excess energy of water through the still basins. Therefore, it has a significant effect on the safety of the dam.
Externí odkaz: https://doaj.org/article/658aa2b316ff4706b0e16030851e135b
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5
Prediction of meteorological drought by using hybrid support vector regression optimized with HHO versus PSO algorithms
Autor: Sani Isah Abba, Shamsuddin Shahid, Anurag Malik, Saad Shauket Sammen, Yazid Tikhamarine
Publikováno v: Environmental Science and Pollution Research. 28:39139-39158
Drought is considered one of the costliest natural disasters that result in water scarcity and crop damage almost every year. Drought monitoring and forecasting are essential for the efficient management of water resources and sustainability in agric
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd33bd7116c929eb559017bcb554446a
https://doi.org/10.1007/s11356-021-13445-0
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6
Support vector regression integrated with novel meta-heuristic algorithms for meteorological drought prediction
Autor: Saad Shauket Sammen, Ozgur Kisi, Doudja Souag-Gamane, Yazid Tikhamarine, Anurag Malik, Priya Rai
Publikováno v: Meteorology and Atmospheric Physics. 133:891-909
Drought is a complex natural phenomenon, so, precise prediction of drought is an effective mitigation tool for measuring the negative consequences on agriculture, ecosystems, hydrology, and water resources. The purpose of this research was to explore
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3d3ba19c5d7dc4abd64a80c1ec953fe4
https://doi.org/10.1007/s00703-021-00787-0
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7
Support vector regression optimized by meta-heuristic algorithms for daily streamflow prediction
Autor: Anurag Malik, Doudja Souag-Gamane, Yazid Tikhamarine, Ozgur Kisi, Quoc Bao Pham
Publikováno v: Stochastic Environmental Research and Risk Assessment. 34:1755-1773
Accurate and reliable prediction of streamflow is vital to the optimization of water resources management, reservoir flood operations, catchment, and urban water management. In this research, support vector regression (SVR) was optimized by six meta-
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6ea7475253c34a6d825a0b9cc7a931ef
https://doi.org/10.1007/s00477-020-01874-1
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8
Artificial intelligence models versus empirical equations for modeling monthly reference evapotranspiration
Autor: Anurag Malik, Doudja Souag-Gamane, Yazid Tikhamarine, Ozgur Kisi
Publikováno v: Environmental Science and Pollution Research. 27:30001-30019
Accurate estimation of reference evapotranspiration (ETo) is profoundly crucial in crop modeling, sustainable management, hydrological water simulation, and irrigation scheduling, since it accounts for more than two-thirds of global precipitation los
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e13f3aa693d5662b4a829167dbc15ac3
https://doi.org/10.1007/s11356-020-08792-3
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9
Predicting daily soil temperature at multiple depths using hybrid machine learning models for a semi-arid region in Punjab, India
Autor: Anurag Malik, Yazid Tikhamarine, Parveen Sihag, Shamsuddin Shahid, Mehdi Jamei, Masoud Karbasi
Publikováno v: Environmental science and pollution research internationalReferences. 29(47)
Prediction of soil temperature (ST) at multiple depths is important for maintaining the physical, chemical, and biological activities in soil for various scientific aspects. The present study was conducted in a semi-arid region of Punjab to predict t
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2e2a0d09d5b90f345b25df32f27c03e
https://pubmed.ncbi.nlm.nih.gov/35597830
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10
Estimation of monthly reference evapotranspiration using novel hybrid machine learning approaches
Autor: Yazid Tikhamarine, Doudja Souag-Gamane, Ozgur Kisi, Anurag Malik, Anil Kumar
Publikováno v: Hydrological Sciences Journal. 64:1824-1842
In this research, five hybrid novel machine learning approaches, artificial neural network (ANN)-embedded grey wolf optimizer (ANN-GWO), multi-verse optimizer (ANN-MVO), particle swarm optimizer (A...
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4ee792dc301a04eb4df96e86683c6521
https://doi.org/10.1080/02626667.2019.1678750
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