Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle

Environmental Research

Volumn 155, Issue , 2017, Pages 141-166

  Deo, Ravinesh C ^a   Downs, Nathan ^a   Parisi, Alfio V ^a   Adamowski, Jan F ^b   Quilty, John M ^b  

^a UNIVERSITY OF SOUTHERN QUEENSLAND   (Australia)

^b MCGILL UNIVERSITY   (Canada)

Author keywords

Extreme learning machine; M5 Model Tree; Multivariate adaptive regression splines; Real time solar forecasting; Solar ultraviolet index (UVI)

Indexed keywords

ALGORITHM; CANCER; CLEAR SKY; DECISION SUPPORT SYSTEM; FORECASTING METHOD; HEALTH RISK; MACHINE LEARNING; ULTRAVIOLET RADIATION; ZENITH ANGLE;

AEROSOL; ARTICLE; DECISION SUPPORT SYSTEM; DECISION TREE; DRAWING; EXTREME LEARNING MACHINE; FORECASTING; MACHINE LEARNING; PRIORITY JOURNAL; RADIOLOGICAL PARAMETERS; SIGMOID; SOLAR ULTRAVIOLET INDEX; SOLAR ZENITH ANGLE; ULTRAVIOLET RADIATION; QUEENSLAND; REPRODUCIBILITY; SUNLIGHT; THEORETICAL MODEL;

AUSTRALIA; QUEENSLAND; TOOWOOMBA;

FORECASTING; MACHINE LEARNING; MODELS, THEORETICAL; QUEENSLAND; REPRODUCIBILITY OF RESULTS; SUNLIGHT; ULTRAVIOLET RAYS;

EID: 85013212376     PISSN: 00139351     EISSN: 10960953     Source Type: Journal    
DOI: 10.1016/j.envres.2017.01.035     Document Type: Article

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