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.
Permanent link to this Catalogue record:
publications.gc.ca/pub?id=9.946439&sl=0
| Department/Agency |
|
|---|---|
| Title | Statistical approaches for estimating industrial water intake in Canada / by Rezvan Taki and Beni Ngabo Nsengiyaremye. |
| Series title |
|
| Publication type | Monograph - View Master Record |
| Language | [English] |
| Other language editions | [French] |
| Format | Digital text |
| Electronic document | |
| Note(s) |
|
| Publishing information |
|
| Author / Contributor |
|
| Description | 1 online resource (14 pages) : graphs. |
| ISBN | 9780660750767 |
| Catalogue number |
|
| Departmental catalogue number | 16-001-M |
| Subject terms |
Request alternate formats
To request an alternate format of a publication, complete the Government of Canada Publications email form. Use the form’s “question or comment” field to specify the requested publication.Page details
- Date modified: