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Evolving fuzzy systems for data streams:A Survey

Dutta Baruah, Rashmi and Angelov, Plamen (2011) Evolving fuzzy systems for data streams:A Survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 1 (6). pp. 461-476.

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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.

Item Type: Article
Journal or Publication Title: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 52193
Deposited By: ep_importer_pure
Deposited On: 21 Dec 2011 08:59
Refereed?: Yes
Published?: Published
Last Modified: 03 Jun 2014 16:36
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/52193

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