Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks
Pattern classification is one of the major components for the design and development of a computerized pattern recognition system. Focused on computational intelligence models, this thesis describes in-depth investigations on two possible directions to design robust and flexible pattern classificati...
Saved in:
Main Author: | F. M., Mohammed |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2014
|
Subjects: | |
Online Access: | http://eprints.usm.my/46164/1/Mohammed%20F.%20M.24.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Fault Detection And Diagnosis Of Induction Motors Using The Fuzzy Min-Max Neural Network And The Classification And Regression Tree
by: Seera, Manjeevan Singh
Published: (2012) -
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) -
A Voting Technique Of Multilayer Perceptron Ensemble For Classification Application
by: Talib, Hafizah
Published: (2014) -
Novel Art-Based Neural Network Models For Pattern Classification, Rule Extraction And Data Regression
by: Yap , Keem Siah
Published: (2010)