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Evolving fuzzy systems for data streams: A Survey

Research output: Contribution to journalJournal article

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Evolving fuzzy systems for data streams : A Survey. / Dutta Baruah, Rashmi; Angelov, Plamen.

In: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Vol. 1, No. 6, 28.11.2011, p. 461-476.

Research output: Contribution to journalJournal article

Harvard

Dutta Baruah, R & Angelov, P 2011, 'Evolving fuzzy systems for data streams: A Survey', Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol. 1, no. 6, pp. 461-476. https://doi.org/10.1002/widm.42

APA

Dutta Baruah, R., & Angelov, P. (2011). Evolving fuzzy systems for data streams: A Survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 1(6), 461-476. https://doi.org/10.1002/widm.42

Vancouver

Dutta Baruah R, Angelov P. Evolving fuzzy systems for data streams: A Survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 2011 Nov 28;1(6):461-476. https://doi.org/10.1002/widm.42

Author

Dutta Baruah, Rashmi ; Angelov, Plamen. / Evolving fuzzy systems for data streams : A Survey. In: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 2011 ; Vol. 1, No. 6. pp. 461-476.

Bibtex

@article{ec5c4ab93fab4ed7919ada0b63ed751f,
title = "Evolving fuzzy systems for data streams: A Survey",
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. ",
author = "{Dutta Baruah}, Rashmi and Plamen Angelov",
year = "2011",
month = nov
day = "28",
doi = "10.1002/widm.42",
language = "English",
volume = "1",
pages = "461--476",
journal = "Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery",
issn = "1942-4787",
publisher = "John Wiley and Sons Inc.",
number = "6",

}

RIS

TY - JOUR

T1 - Evolving fuzzy systems for data streams

T2 - A Survey

AU - Dutta Baruah, Rashmi

AU - Angelov, Plamen

PY - 2011/11/28

Y1 - 2011/11/28

N2 - 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.

AB - 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.

U2 - 10.1002/widm.42

DO - 10.1002/widm.42

M3 - Journal article

VL - 1

SP - 461

EP - 476

JO - Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery

JF - Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery

SN - 1942-4787

IS - 6

ER -