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Développement d'un outil d'aide au diagnostic pour la production de maïs permettant la réduction de la consommation en eaux d'irrigation et en traitements phytosanitaires

Elisa Roux 1
1 LAAS-DISCO - Équipe DIagnostic, Supervision et COnduite
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : My thesis deals with the conception of a decision support tool, and particularly focuses on the aspectsrelative to machine learning and diagnosis. The first goal is to make it capable of selecting thebest scenario for the couple « date of sowing »/ « type of seed » taking in account the plots to diagnosecaracteristics with the aim of guiding the corn farmers practices. The second is goal is about the waterdiagnosis, set up in june, before the irrigation is started. This diagnosis aims at evaluating the waterneeds of large plots areas, with the purpose to anticipate demand and better allocate the water quantityprovided to the farmers. The LAMDA method has been chosen to realize the machine learning ; thisis a fuzzy logic based classification method. A new type of data has been integrated to the method toensure that the main factors that influence a plot yield are fully taken into account. In this process, themachine learning tools have been modelled, implemented, and tested in the order to correspond to thespecific needs of both parts of the project. The new type of data has been designed to be generic andallows a multilayer clustering to diagnose the complex systems. Multidimensional data coming fromvarious contexts are so able to be manage by the LAMDA method. The efficiency of this technique hasbeen assessed on the practical cases of the MAISEO project, but is intented to be apply to every researchfield in which the multivariate classification is used.
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Elisa Roux. Développement d'un outil d'aide au diagnostic pour la production de maïs permettant la réduction de la consommation en eaux d'irrigation et en traitements phytosanitaires. Génie logiciel [cs.SE]. INSA de Toulouse, 2015. Français. ⟨NNT : 2015ISAT0032⟩. ⟨tel-03081156⟩

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