Assessment of groundwater vulnerability using supervised committee to combine fuzzy logic models

Environmental Science and Pollution Research

Volumn 24, Issue 9, 2017, Pages 8562-8577

  Nadiri, Ata Allah ^a   Gharekhani, Maryam ^a   Khatibi, Rahman ^b   Moghaddam, Asghar Asghari ^a  

^a UNIVERSITY OF TABRIZ   (Iran)

^b GTEV ReX Limited   (United Kingdom)

Author keywords

Ardabil aquifer; Fuzzy logic; Supervised committee fuzzy logic (SCFL); Vulnerability index

Indexed keywords

AQUIFER POLLUTION; ARTIFICIAL NEURAL NETWORK; BASELINE CONDITIONS; BASELINE SURVEY; ENVIRONMENTAL ASSESSMENT; FUZZY MATHEMATICS; GROUNDWATER POLLUTION; GROUNDWATER RESOURCE; INDEX METHOD; NUMERICAL MODEL; VULNERABILITY;

ARDABIL; IRAN;

GROUND WATER; NITRIC ACID DERIVATIVE;

ARTIFICIAL NEURAL NETWORK; FUZZY LOGIC; GEOLOGY; HYDROLOGY; IRAN; PREVENTION AND CONTROL; THEORETICAL MODEL; WATER POLLUTION;

FUZZY LOGIC; GEOLOGY; GROUNDWATER; HYDROLOGY; IRAN; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); NITRATES; WATER POLLUTION;

EID: 85012287706     PISSN: 09441344     EISSN: 16147499     Source Type: Journal    
DOI: 10.1007/s11356-017-8489-4     Document Type: Article

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