 Estimation of sky luminance in the tropics using artificial neural networks: Modeling and performance comparison with the CIE modelSerm Janjai and Piyanuch Plaon Applied Energy, 2011, vol. 88, issue 3, 840-847 Abstract: An artificial neural network (ANN) model for estimating sky luminance was developed. A 3-year period (2007-2009) of sky luminance data obtained from measurements at Nakhon Pathom (13.82°N, 100.04°E) and a 1-year period (2008) of the same type of data at Songkhla (7.20°N, 100.60°E), Thailand were used in this study. The ANN model was trained using a back propagation algorithm, based on 2 years data (2007-2008) at Nakhon Pathom for clear, partly cloudy and overcast skies. The trained ANN model was used to predict sky luminance at Nakhon Pathom for the year 2009 for the case of clear, partly cloudy and overcast skies. The results were compared with those of the CIE model. It was found that the ANN model performed better than CIE models for most cases. The ANN model trained with Nakhon Pathom data were also used to predict sky luminance at Songkhla and satisfactory results were obtained. Keywords: Sky; luminance; Daylight; Modeling; Artificial; neural; network; The; tropics; CIE; model (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:88:y:2011:i:3:p:840-847 Ordering information: This journal article can be ordered from Access Statistics for this article Applied Energy is currently edited by J. Yan More articles in Applied Energy from Elsevier |
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