Optimization of drastic method by supervised committee machine artificial intelligence to assess groundwater vulnerability for maragheh-bonab plain aquifer, Iran

Journal of Hydrology

Volumn 503, Issue , 2013, Pages 89-100

  Fijani, Elham ^a,b   Nadiri, Ata Allah ^a,b   Asghari Moghaddam, Asghar ^a   Tsai, Frank T C ^b   Dixon, Barnali ^c  

^a UNIVERSITY OF TABRIZ   (Iran)

^b LOUISIANA STATE UNIVERSITY   (United States)

^c UNIVERSITY OF SOUTH FLORIDA   (United States)

Author keywords

Artificial intelligence; DRASTIC; GIS; Groundwater vulnerability; Multimodel analysis

Indexed keywords

DRASTIC; GROUNDWATER VULNERABILITY; GROUNDWATER VULNERABILITY ASSESSMENTS; LINEAR COMBINATIONS; MULTI-MODEL; OPTIMAL PERFORMANCE; VULNERABILITY ASSESSMENT METHODOLOGIES; VULNERABILITY INDEX;

AQUIFERS; ARTIFICIAL INTELLIGENCE; GEOGRAPHIC INFORMATION SYSTEMS; GROUNDWATER POLLUTION; HEALTH RISKS; OPTIMIZATION; RISK ASSESSMENT; RISK PERCEPTION; WATER WELLS;

GROUNDWATER RESOURCES;

AQUIFER CHARACTERIZATION; ARTIFICIAL INTELLIGENCE; DATA SET; GIS; GROUNDWATER POLLUTION; GROUNDWATER RESOURCE; HYDROLOGICAL MODELING; NITRATE; NUMERICAL MODEL; OPTIMIZATION; RESOURCE ALLOCATION; RISK ASSESSMENT; VULNERABILITY;

BONAB; EAST AZERBAIJAN; IRAN; MARAGHEH;

EID: 84884383148     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2013.08.038     Document Type: Article

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