Predicting groundwater level fluctuations with meteorological effect implications-A comparative study among soft computing techniques

Computers and Geosciences

Volumn 56, Issue , 2013, Pages 32-44

  Shiri, Jalal ^a   Kisi, Ozgur ^b   Yoon, Heesung ^c   Lee, Kang Kun ^d   Hossein Nazemi, Amir ^a  

^a UNIVERSITY OF TABRIZ   (Iran)

^b CANIK BASARI UNIVERSITY   (Turkey)

^c Korea Institute of Geosceince and Mineral Resources   (South Korea)

^d Seoul National University   (South Korea)

Author keywords

ARMA; Artificial intelligence techniques; Groundwater level fluctuations; Prediction

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; ARMA; ARTIFICIAL INTELLIGENCE TECHNIQUES; AUTOREGRESSIVE MOVING AVERAGE; GENE EXPRESSION PROGRAMMING; GROUNDWATER LEVEL FLUCTUATION; GROUNDWATER LEVEL FORECASTING; SUPPORT VECTOR MACHINE TECHNIQUES;

FORECASTING; NEURAL NETWORKS; SOFT COMPUTING; SUPPORT VECTOR MACHINES; WATER SUPPLY;

GROUNDWATER;

ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; COMPARATIVE STUDY; EVAPOTRANSPIRATION; GENE EXPRESSION; GROUNDWATER; PREDICTION; RAINFALL; WATER LEVEL; WATER TABLE;

HONGCHEON; KANGWON; SOUTH KOREA;

EID: 84876308067     PISSN: 00983004     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cageo.2013.01.007     Document Type: Article

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