Greenhouse air temperature modelling with radial basis function neural networks
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 pred...
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| Formato: | conferenceObject |
| Idioma: | eng |
| Publicado em: |
2013
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| Texto completo: | http://hdl.handle.net/10400.1/2303 |
| País: | Portugal |
| Oai: | oai:sapientia.ualg.pt:10400.1/2303 |