A
Ahmad Taher Azar
Researcher at Prince Sultan University
Publications - 458
Citations - 12351
Ahmad Taher Azar is an academic researcher from Prince Sultan University. The author has contributed to research in topics: Computer science & Control theory. The author has an hindex of 47, co-authored 389 publications receiving 8847 citations. Previous affiliations of Ahmad Taher Azar include Misr University for Science and Technology & Yahoo!.
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Journal ArticleDOI
Feature selection via a novel chaotic crow search algorithm
TL;DR: Experimental results reveal the capability of CCSA to find an optimal feature subset which maximizes the classification performance and minimizes the number of selected features, and show that CCSA is superior compared to CSA and the other algorithms.
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Supervised hybrid feature selection based on PSO and rough sets for medical diagnosis
TL;DR: New supervised feature selection methods based on hybridization of Particle Swarm Optimization, PSO based Relative Reduct andPSO based Quick Reduct are presented for the diseases diagnosis, proving the efficiency of the proposed technique as well as enhancements over the existing feature selection techniques.
BookDOI
Chaos Modeling and Control Systems Design
TL;DR: This book is a reference book for graduate students and researchers with a basic knowledge of control theory, computer science and soft-computing techniques and the resulting design procedures are emphasized using Matlab/Simulink software.
BookDOI
Computational Intelligence Applications in Modeling and Control
TL;DR: This book is a reference book for graduate students and researchers with a basic knowledge of control theory, computer science and soft-computing techniques and the resulting design procedures are emphasized using Matlab/Simulink software.
Journal ArticleDOI
Performance analysis of support vector machines classifiers in breast cancer mammography recognition
TL;DR: The experimental results reveal that these SVM classifiers achieve very fast, simple, and efficient breast cancer diagnosis and strongly suggest that LPSVM can aid in the diagnosis of breast cancer.