Susceptibility Prediction of Groundwater Hardness Using Ensemble Machine Learning Models
Susceptibility Prediction of Groundwater Hardness Using Ensemble Machine Learning Models
About this item
Full title
Author / Creator
Publisher
Basel: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Basel: MDPI AG
Subjects
More information
Scope and Contents
Contents
Groundwater resources, unlike surface water, are more vulnerable to disturbances and contaminations, as they take a very long time and significant cost to recover. So, predictive modeling and prevention strategies can empower policymakers for efficient groundwater governance through informed decisions and recommendations. Due to the importance of g...
Alternative Titles
Full title
Susceptibility Prediction of Groundwater Hardness Using Ensemble Machine Learning Models
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2550512152
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2550512152
Other Identifiers
ISSN
2073-4441
E-ISSN
2073-4441
DOI
10.3390/w12102770
