Designing fuzzy inference systems from data: An interpretability-oriented review

Volume: 9, Issue: 3, Pages: 426 - 443
Published: Jun 1, 2001
Abstract
Fuzzy inference systems (FIS) are widely used for process simulation or control. They can be designed either from expert knowledge or from data. For complex systems, FIS based on expert knowledge only may suffer from a loss of accuracy. This is the main incentive for using fuzzy rules inferred from data. Designing a FIS from data can be decomposed into two main phases: automatic rule generation and system optimization. Rule generation leads to a...
Paper Details
Title
Designing fuzzy inference systems from data: An interpretability-oriented review
Published Date
Jun 1, 2001
Volume
9
Issue
3
Pages
426 - 443
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.