Browsing by Author "Al Sukker Akram"

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Browsing by Author "Al Sukker Akram"

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  • A Combined Ant Colony and Differential Evolution Feature Selection Algorithm 
    Al-Jumaily Adel; Khushaba Rami N; Al Sukker Akram; Al-Ani Ahmed (Springer, 2008)
    Feature selection is an important step in many pattern recognition systems that aims to overcome the so-called curse of dimensionality problem. Although Ant Colony Optimization (ACO) proved to be a powerful technique in ...
  • Effect of Feature and channel Selection on EEG Classification 
    Al-Ani Ahmed; Al Sukker Akram (The Institute of Electrical and Electronic Engineers Inc (IEEE), 2006)
    In this paper, we evaluate the significance of feature and channel selection on EEG classification. The selection process is performed by searching the feature/channel space using genetic algorithm, and evaluating the ...
  • Enhanced Feature Selection Algorithm Using Ant Colony Optimization and Fuzzy Memberships 
    Al Sukker Akram; Khushaba Rami N; Al-Ani Ahmed; Al-Jumaily Adel (IASTED, 2008)
    Feature selection is an indispensable pre-processing step when mining huge datasets that can significantly improve the overall system performance. This paper presents a novel feature selection method that utilizes both the ...
  • An Enhanced Neural Network Ensemble for Automatic Sleep Scoring 
    Al Sukker Akram; Al-Ani Ahmed (IEEE Xplore, 2011)
    Improving the diversity of Neural Network Ensembles (NNE) plays an important role in creating robust classification systems in many fields. Several methods have been proposed in the literature to create such diversity using ...
  • Evaluation of Feature Selection Methods for Improved EEG Classification 
    Al Sukker Akram; Al-Ani Ahmed (Research Publishing Services, 2006)
    This paper compares several methods for feature selection used in EEG classification. Sequential, heuristics and population-based search methods are compared according to their efficiency and computational cost A support ...
  • Intelligent Artificial Ants based Feature Extraction from Wavelet Packet Coefficients for Biomedical Signal Classification 
    Al-Jumaily Adel; Khushaba Rami N; Al-Ani Ahmed; Al Sukker Akram (IEEE, 2008)
    n this paper, a new feature extraction method utilizing ant colony optimization in the selection of wavelet packet transform (WPT) best basis is presented and adopted in classifying biomedical signals. The new algorithm, ...
  • A Modified K-Nearest Neighbor Classifier to Deal with Unbalanced Classes 
    Al Sukker Akram; Al-Ani Ahmed; Atiya Amir (INSTICC - Institute for Systems and Technologies of Information, Control and Communication, 2009)
    We present in this paper a simple, yet valuable improvement to the traditional k-Nearest Neighbor (kNN) classifier. It aims at addressing the issue of unbalanced classes by maximizing the class-wise classification accuracy. ...
  • A Novel Swarm-Based Feature Selection Algorithm in Multifunction Myoelectric Control 
    Zomaya Albert; Al-Jumaily Adel; Khushaba Rami N; Al-Ani Ahmed; Al Sukker Akram (IOS Press, 2009)
    Accurate and computationally efficient myoelectric control strategies have been the focus of a great deal of research in recent years. Although many attempts exist in literature to develop such strategies, deficiencies ...
  • Optimising the K-NN Metric Weights Using Differential Evolution 
    Al Sukker Akram; Khushaba Rami N; Al-Ani Ahmed (IEEE, 2010)
    Traditional k-NN classifier poses many limitations including that it does not take into account each class distribution, importance of each feature, contribution ofeach neighbor, and the number ofinstances for each class. ...