Combination of discretization regression with data-driven algorithms for modeling irrigation water quality indices

Forecasting water quality parameters helps plan crop selection and irrigation strategies but is often costly because many parameters are required, particularly in developing nations. Therefore, the current research objective is to estimate the irrigation water quality indices in the Nand Samand catc...

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Vydané v:	Ecological informatics Ročník 75; s. 102093
Hlavní autori:	Dimple, Singh, Pradeep Kumar, Rajput, Jitendra, Kumar, Dheeraj, Gaddikeri, Venkatesh, Elbeltagi, Ahmed
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.07.2023
Predmet:	forests irrigation Irrigation water Kelly's ratio Machine learning magnesium Magnesium hazards sodium Sodium adsorption ratio statistics water quality watersheds PRM Irrigation water GPS Magnesium hazards Sodium adsorption ratio ‘ MH ML REGD-RSS WHO NSE % Eqs & MPUAT AI MAPE BCM POM MAE CGWB ° RRSE Contd KR/KI Deptt Kelly's ratio SAR E CTAE REGD-AR N SD MBE SE REGD-RF G.B REGD-M5P IWQ km LULC IWQI d Fig MSL KGE ICAR RMSE IARI m SSP r Mm3 FAO REGD APHA Machine learning RAE
ISSN:	1574-9541
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