Daily UV radiation modeling with the usage of statistical correlations and artificial neural networks

Renewable Energy

Volumn 36, Issue 12, 2011, Pages 3337-3344

  Leal, S S ^a   Tiba C ^b   Piacentini, R ^c  

^a INSTITUTO FEDERAL DE EDUCAÇÃO   (Brazil)

^b FEDERAL UNIVERSITY OF PERNAMBUCO   (Brazil)

^c INSTITUTO DE FÍSICA ROSARIO   (Argentina)

Author keywords

Artificial neural networks; Daily UV irradiation; Statistical model; Transmittance index

Indexed keywords

AIR MASS; ATMOSPHERIC TRANSMITTANCE; GLOBAL IRRADIATION; GLOBAL RADIATION; GLOBAL RADIATION DATA; GLOBAL SOLAR IRRADIATION; HORIZONTAL PLANES; LINEAR CORRELATION; MEASURING STATIONS; MULTIPLE REGRESSIONS; PARAMETRIC MODELS; PERNAMBUCO; PHYSICAL VARIABLES; SIMULTANEOUS MEASUREMENT; SOLAR UV RADIATION; STATISTICAL CORRELATION; STATISTICAL MODELS; STATISTICAL PERFORMANCE; TEMPORAL COVERAGE; TIME-PERIODS; TRANSMITTANCE INDEX; TYPICAL CLIMATES; UV IRRADIATION; UV SOLAR RADIATION;

ATMOSPHERIC RADIATION; ESTIMATION; IRRADIATION; SOLAR RADIATION; STATISTICS; SUN; ULTRAVIOLET RADIATION;

NEURAL NETWORKS;

AIR MASS; ARTIFICIAL NEURAL NETWORK; CORRELATION; DATA SET; IRRADIANCE; MULTIPLE REGRESSION; NUMERICAL MODEL; REGIONAL CLIMATE; SOLAR RADIATION; TRANSMITTANCE; ULTRAVIOLET RADIATION; WEATHER STATION;

BRAZIL;

EID: 79960177524     PISSN: 09601481     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.renene.2011.05.007     Document Type: Article

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