Clear-sky solar luminous efficacy determination using artificial neural networks-Reference-Cited by-同舟云学术

Clear-sky solar luminous efficacy determination using artificial neural networks

Published:2007-07 Issue:7 Volume:81 Page:929-939
ISSN:0038-092X
Container-title:Solar Energy
language:en
Short-container-title:Solar Energy

Author:

López Gabriel,Gueymard Christian A.

Publisher

Elsevier BV

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment

Reference34 articles.

1. Aydinli, S., 1979. Strahlungsphysikalische und Lichttechnische Daten des Tageslichtes, rep. CIE TC-4.2, Commission Internationale de l’Eclairage.

2. Aydinli, S., Krochmann, J., 1983. Data on Daylight and Solar Radiation: Guide on Daylight. Draft for CIE TC 4.2, Commission Internationale de l’Eclairage, Paris.

3. Dogniaux, R., 1973. Standardization of methods of measurement and calculation of climatological data for thermal and day-light applications, Symp. on Solar Radiation, Rockville, MD.

4. Dogniaux, R., 1974. Représentations analytiques des composantes du rayonnement lumineux solaire, Publ. A83, Institut Royal Météorologique de Belgique.

5. Practical Methods of Optimization;Fletcher,1987

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