Click on “Download PDF” for the PDF version or on the title for the HTML version.

If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options.

Solar Radiation Prediction Methods Applied to Improve Greenhouse Climate Control

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Pp. 154-160 in Proceedings of the World Congress of Computers in Agriculture and Natural Resources (13-15, March 2002, Iguacu Falls, Brazil)  701P0301.(doi:10.13031/2013.8324)
Authors:   J.P. Coelho, J.Boaventura Cunha and P.B. de Moura Oliveira
Keywords:   Time Series Prediction, Horticulture, Artificial Neural Networks, Linear Regression

In this paper, deterministic and Artificial Neural Networks (ANNs) based techniques are applied to generate solar radiation forecasts with the purpose of being incorporated within a greenhouse predictive control strategy. These predictions are essential to estimate heat load fluctuations in the greenhouse caused by high frequency solar radiation changes, and so to improve ventilation and heating computation requirements for the greenhouse.

(Download PDF)    (Export to EndNotes)