Home > Research > Publications & Outputs > Evolving fuzzy systems for data streams
View graph of relations

Evolving fuzzy systems for data streams: A Survey

Research output: Contribution to journalJournal article

Published
Close
<mark>Journal publication date</mark>28/11/2011
<mark>Journal</mark>Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Issue number6
Volume1
Number of pages16
Pages (from-to)461-476
<mark>State</mark>Published
Early online date28/07/11
<mark>Original language</mark>English

Abstract

Evolving fuzzy systems (EFSs) can be regarded as intelligent systems based on fuzzy rule-based or neuro-fuzzy models with the ability to learn continuously and to gradually develop with the objective of enhancing their performance. Such systems learn in online mode by analyzing incoming samples, and adjusting both structure and parameters. The objective of this chapter is to present a brief overview of some early as well as recent EFSs by focusing on their architecture, design algorithms along with the merits and demerits, and various applications.