Interpretable fuzzy inference systems for cooperation of expert knowledge and data in agricultural applications using FisPro
Identifieur interne : 001372 ( Main/Exploration ); précédent : 001371; suivant : 001373Interpretable fuzzy inference systems for cooperation of expert knowledge and data in agricultural applications using FisPro
Auteurs : Serge Guillaume [France] ; Brigitte Charnomordic [France]Source :
- Proceedings of IEEE International Conference on Fuzzy Systems [ 1098-7584 ] ; 2010.
Abstract
Fuzzy inference systems (FIS) can either be designed from expert knowledge or learnt from data. The main interest of using FIS is their interpretability. An open source software called FisPro has been designed to answer precisely the needs of interpretable FIS design and learning. This work presents FisPro and illustrates through three real world applications how to cope with the different types of information while preserving interpretability, whatever the respective contributions of expertise and data in the FIS design.
Url:
DOI: 10.1109/FUZZY.2010.5584673
Affiliations:
- France
- Hérault (département), Languedoc-Roussillon, Occitanie (région administrative)
- Montpellier
- Institut national de la recherche agronomique
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Le document en format XML
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<front><div type="abstract" xml:lang="en">Fuzzy inference systems (FIS) can either be designed from expert knowledge or learnt from data. The main interest of using FIS is their interpretability. An open source software called FisPro has been designed to answer precisely the needs of interpretable FIS design and learning. This work presents FisPro and illustrates through three real world applications how to cope with the different types of information while preserving interpretability, whatever the respective contributions of expertise and data in the FIS design. </div>
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