Hourly photosynthetically active radiation estimation in Midwestern United States from artificial neural networks and conventional regressions models-Reference-Cited by-同舟云学术

Hourly photosynthetically active radiation estimation in Midwestern United States from artificial neural networks and conventional regressions models

Published:2015-12-29 Issue:8 Volume:60 Page:1247-1259
ISSN:0020-7128
Container-title:International Journal of Biometeorology
language:en
Short-container-title:Int J Biometeorol

Author:

Yu Xiaolei,Guo Xulin

Funder

China Scholarship Council (CN)

Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada (CA)

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Atmospheric Science,Ecology

Link

http://link.springer.com/content/pdf/10.1007/s00484-015-1120-9.pdf

Reference52 articles.

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3. Alados I, Iy F-M, Alados-Arboledas L (1996) Photosynthetically active radiation: measurements and modelling. Agric For Meteorol 78(1):121–131

4. Alados I, Olmo FJ, Foyo-Moreno I, Alados-Arboledas L (2000) Estimation of photosynthetically active radiation under cloudy conditions. Agric Forest Meteorol 102(1):39–50. doi: 10.1016/S0168-1923(00)00091-5

5. Augustine JA, DeLuisi JJ, Long CN (2000) SURFRAD—a national surface radiation budget network for atmospheric research. Bull Am Meteorol Soc 81(10):2341–2357

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