Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
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
IS - 6
ER -