Artificial neural network modeling for identification of unknown pollution sources in groundwater with partially missing concentration observation data

Water Resources Management

Volumn 21, Issue 3, 2007, Pages 557-572

  Singh, Raj Mohan ^a   Datta, Bithin ^b  

^a MOTILAL NEHRU NATIONAL INSTITUTE OF TECHNOLOGY   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY KANPUR   (India)

Author keywords

Artificial neural networks; Concentration patterns; Groundwater pollution; Inverse problem; Measurement error; Missing observation; Pollution source identification

Indexed keywords

BACKPROPAGATION ALGORITHMS; COMPUTER SIMULATION; GROUNDWATER FLOW; INVERSE PROBLEMS; MEASUREMENT ERRORS; NEURAL NETWORKS;

CONCENTRATION PATTERNS; POLLUTION SOURCE IDENTIFICATION;

GROUNDWATER POLLUTION;

BACKPROPAGATION ALGORITHMS; COMPUTER SIMULATION; GROUNDWATER FLOW; GROUNDWATER POLLUTION; INVERSE PROBLEMS; MEASUREMENT ERRORS; NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; GROUNDWATER FLOW; GROUNDWATER POLLUTION; INVERSE PROBLEM; NUMERICAL MODEL; PERFORMANCE ASSESSMENT; POLLUTANT SOURCE; POLLUTANT TRANSPORT; SPATIOTEMPORAL ANALYSIS;

EID: 33947708401     PISSN: 09204741     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11269-006-9029-z     Document Type: Article

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