Evaluating the accuracy of ANN and LR models to estimate the water quality in Zarivar International Wetland, Iran

Natural Hazards

Volumn 85, Issue 3, 2017, Pages 1511-1527

  Amanollahi, Jamil ^a   Kaboodvandpour, Shahram ^a   Majidi, Hiva ^a  

^a UNIVERSITY OF KURDISTAN   (Iran)

Author keywords

Chemical and physical; Chlorophyll; Model; Remote sensing; Turbidity; Wetland

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CHLOROPHYLL; REGRESSION ANALYSIS; REMOTE SENSING; TURBIDITY; WATER QUALITY; WETLAND;

IRAN;

EID: 84995393583     PISSN: 0921030X     EISSN: 15730840     Source Type: Journal    
DOI: 10.1007/s11069-016-2641-1     Document Type: Article

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