Field-scale application of three types of neural networks to predict ground-water levels

Journal of the American Water Resources Association

Volumn 43, Issue 5, 2007, Pages 1245-1256

  Asefa, Tirusew ^a   Wanakule, Nisai ^a   Adams, Alison ^a  

^a Department of Source Rotation and Environmental Protection ^*  (United States)

Author keywords

Artificial neural networks; Generalized regression network; Ground water level prediction; Radial basis networks; Tampa Bay Water

Indexed keywords

ALGORITHMS; NEURAL NETWORKS; REGRESSION ANALYSIS; SIGNAL FILTERING AND PREDICTION; WATER LEVELS;

GENERALIZED REGRESSION NETWORK; GROUND WATER LEVEL PREDICTION;

GROUNDWATER;

ALGORITHMS; GROUNDWATER; NEURAL NETWORKS; REGRESSION ANALYSIS; SIGNAL FILTERING AND PREDICTION; WATER LEVELS;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; FIELD METHOD; GROUNDWATER; WATER LEVEL;

EID: 34548690772     PISSN: 1093474X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1752-1688.2007.00107.x     Document Type: Article

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