Prediction of daily dewpoint temperature using a model combining the support vector machine with firefly Algorithm

Journal of Irrigation and Drainage Engineering

Volumn 142, Issue 5, 2016, Pages

  Al Shammari, Eiman Tamah ^a   Mohammadi, Kasra ^b   Keivani, Afram ^c   Hamid, Siti Hafizah Ab ^d   Akib, Shatirah ^e   Shamshirband, Shahaboddin ^d   Petkovíc, Dalibor ^f  

^a KUWAIT UNIVERSITY   (Kuwait)

^b University of Massachusetts   (United States)

^c ISLAMIC AZAD UNIVERSITY   (Iran)

^d UNIVERSITY OF MALAYA   (Malaysia)

^e HERIOT WATT UNIVERSITY MALAYSIA   (Malaysia)

^f UNIVERSITY OF NI   (Serbia)

Author keywords

Dew point temperature; Firefly algorithm; Hybrid model; Prediction; Support vector machine

Indexed keywords

ALGORITHMS; ATMOSPHERIC HUMIDITY; ATMOSPHERIC PRESSURE; ATMOSPHERIC TEMPERATURE; BIOLUMINESCENCE; FORECASTING; GENETIC ALGORITHMS; GENETIC PROGRAMMING; MEAN SQUARE ERROR; NEURAL NETWORKS; OPTIMIZATION;

AVERAGE AIR TEMPERATURE; CORRELATION COEFFICIENT; DEWPOINT TEMPERATURE; FIREFLY ALGORITHMS; HYBRID APPROACH; HYBRID MODEL; ITS EFFICIENCIES; ROOT MEAN SQUARE ERRORS;

SUPPORT VECTOR MACHINES;

AIR TEMPERATURE; ALGORITHM; ATMOSPHERIC PRESSURE; CLIMATE MODELING; CLIMATE PREDICTION; DEW POINT; RELATIVE HUMIDITY; SUPPORT VECTOR MACHINE;

IRAN;

EID: 84964727663     PISSN: 07339437     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)IR.1943-4774.0001015     Document Type: Article

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