HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Theses

Induction de règles floues interprétables

Abstract : This report deals with interpretable fuzzy rule induction from data for human-computer cooperation purposes. A review of fuzzy rule induction methods shows that they can be grouped into three families. Their comparison highlights the fact that the interpretability is not guaranteed. The central part of our work is a new fuzzy rule induction method. It aims to fulfill three interpretability conditions: readable fuzzy partitions, a number of rules as small as possible, incomplete rules. This is achieved through a three step procedure: generating a family of fuzzy partitions for each input variable, building an accurate fuzzy inference system, simplifying the rule base. The procedure is based on original concepts such as a metric distance suitable for fuzzy partitioning, and the input context defined by a set of rules. We introduced coverage and heterogeneity related indices to guide the prodedure, complementary with a numerical performance index. The method is first validated using well known data and then applied to decison making in a complex system. This application means to extract winemaking rules which enhance the color of red wine.
Keywords : thesis
Document type :
Theses
Complete list of metadata

https://hal.inrae.fr/tel-02580417
Contributor : Migration Irstea Publications Connect in order to contact the contributor
Submitted on : Thursday, May 14, 2020 - 8:23:47 PM
Last modification on : Friday, May 15, 2020 - 2:11:17 AM

File

pub00010120.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : tel-02580417, version 1
  • IRSTEA : PUB00010120

Collections

Citation

S. Guillaume. Induction de règles floues interprétables. Sciences de l'environnement. Doctorat, spécialité Systèmes informatiques, INSA Toulouse, 2001. Français. ⟨tel-02580417⟩

Share

Metrics

Record views

11

Files downloads

3