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.
Full text not available from this repository.Official URL: http://dx.doi.org/10.1002/widm.42
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: | 31 Aug 2012 09:21 |
| Identification Number: | |
| URI: | http://eprints.lancs.ac.uk/id/eprint/52193 |
Actions (login required)
| View Item |
