Statistical approaches for estimating industrial water intake in Canada / by Rezvan Taki and Beni Ngabo Nsengiyaremye. : CS16-001/2025-2E-PDF

"The reliable estimation of industrial water use is critical for establishing realistic water conservation goals in Canada’s manufacturing sector, mineral extraction industries and thermal-electric power generation sector. To evaluate the predictive accuracy of several statistical models at the national level, this study uses survey data to explore modelling techniques including the eXtreme Gradient Boosting (XGBoost) model, the Thin-Plate Spline (TPSPLINE) model, Multiple Imputation by Chained Equations (MICE), linear regression, partial least squares (PLS) regression, and least absolute shrinkage and selection operator (LASSO) regression"--Abstract, page 3.

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