Interpretability in Fuzzy Systems Optimization: A Topological Approach

Ricardo de Aldama, Michaël Aupetit

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

When dealing with complex problems, it is often the case that fuzzy systems must undergo an optimization process. During this process, the preservation of interpretability is a major concern. Here we present a new mathematical framework to analyze the notion of interpretability of a fuzzy partition, and a generic algorithm to preserve it. This approach is rather flexible and it helps to highly automatize the optimization process. Some tools come from the field of algebraic topology.

Original languageEnglish
Title of host publicationInformation Processing and Management of Uncertainty in Knowledge-Based Systems - 15th International Conference, IPMU 2014, Proceedings
PublisherSpringer Verlag
Pages588-597
Number of pages10
EditionPART 1
ISBN (Print)9783319087948
DOIs
Publication statusPublished - 1 Jan 2014
Event15th International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems, IPMU 2014 - Montpellier, France
Duration: 15 Jul 201419 Jul 2014

Publication series

NameCommunications in Computer and Information Science
NumberPART 1
Volume442 CCIS
ISSN (Print)1865-0929

Conference

Conference15th International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems, IPMU 2014
CountryFrance
CityMontpellier
Period15/7/1419/7/14

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Keywords

  • algebraic topology
  • fuzzy partition
  • fuzzy system
  • interpretability
  • optimization
  • tuning

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

Cite this

de Aldama, R., & Aupetit, M. (2014). Interpretability in Fuzzy Systems Optimization: A Topological Approach. In Information Processing and Management of Uncertainty in Knowledge-Based Systems - 15th International Conference, IPMU 2014, Proceedings (PART 1 ed., pp. 588-597). (Communications in Computer and Information Science; Vol. 442 CCIS, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-319-08795-5_60