Name
Abstract | ||
|---|---|---|
Modern greenhouse climate controllers are based on models in order to simulate and predict the greenhouse environment behaviour. These models must be able to describe indoor climate process dynamics, which are a function of both the control actions taken and the outside climate. Moreover, if predictive or feedforward control techniques are to be applied, it is necessary to employ models to describe and predict the weather. From all the climate variables, solar radiation is the one with greater impact in the greenhouse heat load. Hence, making good predictions of this physical quantity is of extreme importance. In this paper, the solar radiation is represented as a time-series and a support vector regression model is used to make long term predictions. Results are compared with the ones achieved by using other type of models, both linear and non-linear. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-13161-5_15 | SOFT COMPUTING MODELS IN INDUSTRIAL AND ENVIRONMENTAL APPLICATIONS |
Keywords | Field | DocType |
support vector regression,time series,feedforward control,solar radiation | Mathematical optimization,Physical quantity,Computer science,Support vector machine,Process dynamics,Greenhouse,Heat load,Feed forward | Conference |
Volume | ISSN | Citations |
73 | 1867-5662 | 2 |
PageRank | References | Authors |
0.40 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| João Paulo Coelho | 1 | 6 | 2.50 |
| J. Boaventura Cunha | 2 | 25 | 8.22 |
| Paulo B. de Moura Oliveira | 3 | 30 | 9.66 |
| E. J. Solteiro Pires | 4 | 81 | 13.95 |