caa a22 4500 445800607 CHVBK 20180317145139.0 cr unu---uuuuu 170323e20111001xx s 000 0 eng 10.1007/s00704-010-0392-6 doi (NATIONALLICENCE)springer-10.1007/s00704-010-0392-6 Sensitivity analysis of climatic parameters for sky classification [Elektronische Daten] [D. Li, H. Tang, K. Cheung, E. Lee, C. Cheng] Climatic variables are frequently used as weighting factors to indicate the degree of clearness for interpreting sky patterns. However, such important parameters are not always widely available and their criteria to define a sky condition are not clear-cut. In addition, certain variables may be more effective than the others in terms of sky identification. This paper studies the capability of various daylight parameters, namely zenith luminance, global, direct-beam and sky-diffuse illuminance, and solar altitude for categorizing the 15 International Commission on Illumination (CIE) standard skies. A new form of artificial neural networks called probabilistic neural network (PNN) which is a powerful technique for pattern recognition was used for the analysis. The findings suggested that the PNN is an appropriate tool when a number of climatic parameters of various criteria for differentiating sky standards are employed, and the ratio of zenith luminance to diffuse illuminance (L z/D v) and solar altitude (α s) are respectively the most and the least significant input parameters for discriminating between the 15 CIE skies. Springer-Verlag, 2011 Li D. Building Energy Research Group, Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, China aut Tang H. Building Energy Research Group, Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, China aut Cheung K. Building Energy Research Group, Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, China aut Lee E. Building Energy Research Group, Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, China aut Cheng C. Building Energy Research Group, Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, China aut Theoretical and Applied Climatology Springer Vienna 105/3-4(2011-10-01), 297-309 0177-798X 105:3-4<297 2011 105 704 https://doi.org/10.1007/s00704-010-0392-6 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00704-010-0392-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Li D. Building Energy Research Group, Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, China aut NATIONALLICENCE 700 1- Tang H. Building Energy Research Group, Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, China aut NATIONALLICENCE 700 1- Cheung K. Building Energy Research Group, Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, China aut NATIONALLICENCE 700 1- Lee E. Building Energy Research Group, Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, China aut NATIONALLICENCE 700 1- Cheng C. Building Energy Research Group, Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, China aut NATIONALLICENCE 773 0- Theoretical and Applied Climatology Springer Vienna 105/3-4(2011-10-01), 297-309 0177-798X 105:3-4<297 2011 105 704 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer