Fuzzy Min-Max Classifier Based on New Membership Function for Pattern Classification: A Conceptual Solution
The fuzzy min-max (FMM) neural network is one of the most powerful neural networks that combines neural network and fuzzy set theory into a common framework for tackling pattern classification problems. FMM neural network carries out learning processes that consist of hyperbox expansion, hyperbox ov...
Saved in:
Main Authors: | Alhroob, Essam, Ngahzaifa, Ab. Ghani |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
IEEE
2018
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/25103/1/Green%20sonochemical%20synthesis%20of%20few1.pdf http://umpir.ump.edu.my/id/eprint/25103/ https://doi.org/10.1109/ICCSCE.2018.8685029 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Critical Review on Selected Fuzzy Min-Max Neural Networks and Their Significance and Challenges in Pattern Classification
by: Alhroob, Essam, et al.
Published: (2019) -
Modern fuzzy min max neural networks for pattern classification
by: Al Sayaydeh, Osama Nayel Ahmad
Published: (2019) -
Flexible enhanced fuzzy min–max neural network model for pattern classification problems
by: Al-Hroob, Essam Muslem Harb
Published: (2020) -
Analysis on Misclassification in Existing Contraction of Fuzzy Min–max Models
by: Alhroob, Essam, et al.
Published: (2020) -
A survey of fuzzy min max neural networks for pattern classification: variants and applications
by: Al Sayaydeh, Osama Nayel, et al.
Published: (2018)