A Critical Review on Selected Fuzzy Min-Max Neural Networks and Their Significance and Challenges in Pattern Classification
At present, pattern classification is one of the most important aspects of establishing machine intelligence systems for tackling decision-making processes. The fuzzy min-max (FMM) neural network combines the operations of an artificial neural network and fuzzy set theory into a common framework. FM...
Saved in:
Main Authors: | Alhroob, Essam, Mohammed, Mohammed Falah, Lim, Chee Peng, Tao, Hai |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/25102/1/A%20Critical%20Review%20on%20Selected%20Fuzzy%20Min-Max.pdf http://umpir.ump.edu.my/id/eprint/25102/ https://doi.org/10.1109/ACCESS.2019.2911955 https://doi.org/10.1109/ACCESS.2019.2911955 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A survey of fuzzy min max neural networks for pattern classification: variants and applications
by: Al Sayaydeh, Osama Nayel, et al.
Published: (2018) -
Fuzzy Min-Max Classifier Based on New Membership Function for Pattern Classification: A Conceptual Solution
by: Alhroob, Essam, et al.
Published: (2018) -
Improving the Fuzzy Min-Max Neural Network with a K-nearest Hyperbox Expansion Rule for Pattern Classification
by: Mohammed, Mohammed Falah, et al.
Published: (2017) -
An Ensemble of Enhanced Fuzzy Min Max Neural Networks for Data Classification
by: Mohammed, Mohammed Falah, et al.
Published: (2017) -
Modern fuzzy min max neural networks for pattern classification
by: Al Sayaydeh, Osama Nayel Ahmad
Published: (2019)