Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.1/2303
Título: Greenhouse air temperature modelling with radial basis function neural networks
Autor: Ferreira, P. M.
Ruano, A. E.
Palavras-chave: Neural Networks
Greenhouse Environmental Control
Modelling
Radial Basis
Data: 2001
Citação: Ferreira, P. M.; Ruano, A. E. Greenhouse Air Temperature Modelling with Radial Basis Function Neural Networks, Trabalho apresentado em Management, Identification and Control of Agriculture Buildings, In Management, Identification and Control of Agriculture Buildings, Vila Real, 2001.
Resumo: Results on the application of radial basis function neural networks to model the inside air temperature of a hydroponic greenhouse as a function of the outside air temperature and solar radiation, and the inside relative humidity, are presented. As the model is intended to be incorporated in an predictive control strategy both off-line and on-line methods are important to accomplish this task. In this paper hybrid off-line training methods and on-line learning algorithms are analysed. Results from a previously presented off-line method and its application to on-line learning are also presented. It exploits the linear-nonlinear structure found in radial basis function neural networks.
Peer review: yes
URI: http://hdl.handle.net/10400.1/2303
Aparece nas colecções:FCT2-Artigos (em revistas ou actas indexadas)

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