Evolving possibilistic fuzzy modelling

DOI10.1080/00949655.2016.1270281OpenAlexW2563456943MaRDI QIDQ5106863

Rosangela Ballini, Leandro Maciel, Fernando Gomide

Publication date: 22 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2016.1270281

zbMATH Keywords

forecastingfuzzy system modelsparticipatory learningpossibilistic fuzzy clusteringevolving modelling

Mathematics Subject Classification ID

Fuzzy control/observation systems (93C42) Theory of fuzzy sets, etc. (03E72) Fuzzy analysis in statistics (62A86)

Uses Software

• DENFIS

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• On possibilistic clustering with repulsion constraints for imprecise data
• Evolving fuzzy systems -- methodologies, advanced concepts and applications.
• An approach for on-line extraction of fuzzy rules using a self-organising fuzzy neural network
• Inference using compiled min-based possibilistic causal networks in the presence of interventions
• Naive possibilistic classifiers for imprecise or uncertain numerical data
• Time-series forecasting with a novel fuzzy time-series approach: an example for Istanbul stock market
• Fuzzy parametric sample selection model: Monte Carlo simulation approach
• Oscillation and Chaos in Physiological Control Systems
• Time-varying neuro-fuzzy model using probability density function techniques for batch processes

This page was built for publication: Evolving possibilistic fuzzy modelling