Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.1/2270
Título: Soft-computing methods in greenhouse environmental and crop modelling
Autor: Ferreira, P. M.
Ruano, A. E.
Palavras-chave: Greenhouse environmental modelling
Crop growth modelling
Soft computing methods
Data: 2005
Citação: Ferreira, P. M.; Ruano, A. E. Soft-computing methods in greenhouse environmental and crop modelling. Trabalho apresentado em he 5th Conference of the European Federation for Information Technology in Agriculture, Food and Environment, and the 3th World Congress on Computers in Agriculture and Natural Resources, In Proceedings of the 5th Conference of the European Federation for Information Technology in Agriculture, Food and Environment, and the 3th World Congress on Computers in Agriculture and Natural Resources, Vila Real, 2005.
Resumo: This paper presents results regarding ongoing experimental research in a hydroponic greenhouse located at the University of Algarve in the South of Portugal. The work focuses on environmental predictive control and production optimisation for a tomato crop. Recent results on the application of Soft- Computing methods to external climate predictive models, and also on strategies for tomato growth modelling are presented. The climate and environmental quantities are modelled by using radial basis function neural networks whose input-output structure is selected by a multi-objective genetic algorithm. Image processing methods are applied to the extraction of plant features from pictures taken periodically.
Peer review: yes
URI: http://hdl.handle.net/10400.1/2270
Aparece nas colecções:FCT2-Artigos (em revistas ou actas indexadas)

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