Application of radial basis function neural networks to a greenhouse inside air temperature model
The problem with the adequacy of radial basis function neural networks to model the inside air temperature as a function of the outside air temperature and solar radiation, and the inside relative humidity in an hydroponic greenhouse is addressed.
| Autor principal: | |
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| Outros Autores: | , |
| Formato: | conferenceObject |
| Idioma: | eng |
| Publicado em: |
2013
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/10400.1/2161 |
| País: | Portugal |
| Oai: | oai:sapientia.ualg.pt:10400.1/2161 |