Systèmes d'inférence floue : collaboration expertise et données dans un environnement de modélisation intégrée à l'aide de FisPro

Fuzzy inference systems are likely to play a significant part in system modeling, when data and expert knowledge integration is important. The aim of this paper is to set up some guidelines for this kind of modeling, based on practical experience in the fields of Agronomy and Environment. We dicuss fuzzy system assets, their ability for data and expert knowledge integration in a common framework, and their position relatively to other models. The open source FisPro implementation is presented and the approach is illustrated through two detailed case studies. RÉSUMÉ. Les systèmes d’inférence floue peuvent avoir une place importante dans un processus de modélisation, quand l’intégration de données et d’expertise est nécessaire. L’objectif de cet article est de donner des lignes directrices pour ce type de modélisation, basées sur notre expérience pratique dans les domaines de l’agronomie et de l’environnement. Nous discutons les points originaux de ces systèmes, leur capacité à intégrer expertise et données dans un cadre commun, ainsi que leur place par rapport à d’autres modèles. L’implémentation dans le logiciel open source FisPro est également présentée et deux cas d’étude illustrent l’approche.

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