Greenhouse Heat Load Prediction Using a Support Vector Regression Model

  • João Paulo Coelho
  • José Boaventura Cunha
  • Paulo de Moura Oliveira
  • Eduardo Solteiro Pires
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 73)


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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • João Paulo Coelho
    • 1
  • José Boaventura Cunha
    • 2
  • Paulo de Moura Oliveira
    • 2
  • Eduardo Solteiro Pires
    • 3
  1. 1.CITAB - Centro de Investigação e de Tecnologias Agro-Ambientais e BiológicasInstituto Politécnico de BragançaBragançaPortugal
  2. 2.Dep. EngenhariasUniversidade de Trás-os-Montes e Alto DouroVila RealPortugal
  3. 3.CITAB - Centro de Investigação e de Tecnologias Agro-Ambientais e BiológicasUniversidade de Trás-os-Montes e Alto Douro, Dep. EngenhariasVila RealPortugal

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