Treffer: Groundwater quality modeling and determining critical points: a comparison of machine learning to Best-Worst Method.

Groundwater quality modeling and determining critical points: a comparison of machine learning to Best-Worst Method.

Nasiri Khiavi A; Department of Watershed Management Engineering, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor, Iran., Mostafazadeh R; Department of Natural Resources and Member of Water Managements Research Center, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran. raoofmostafazadeh@uma.ac.ir., Adhami M; Department of Watershed Management Engineering, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor, Iran.

Environmental science and pollution research international [Environ Sci Pollut Res Int] 2023 Nov; Vol. 30 (54), pp. 115758-115775. Date of Electronic Publication: 2023 Oct 27.

Journal Article

English

Publisher: Springer Country of Publication: Germany NLM ID: 9441769 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1614-7499 (Electronic) Linking ISSN: 09441344 NLM ISO Abbreviation: Environ Sci Pollut Res Int Subsets: MEDLINE

Publication: <2013->: Berlin : Springer
Original Publication: Landsberg, Germany : Ecomed

Water Pollutants, Chemical*/analysis , Groundwater*, Water Quality ; Environmental Monitoring/methods ; Bayes Theorem ; Sulfates/analysis ; Chlorides ; Machine Learning

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Keywords: Geospatial modeling; Groundwater pollution; Groundwater resources; MCDM; Water quality

0 (Water Pollutants, Chemical)
0 (Sulfates)
0 (Chlorides)

Date Created: 20231027 Date Completed: 20231129 Latest Revision: 20231205

20250114

10.1007/s11356-023-30530-8

37889408

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