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  1. 1
    Formulating new enhanced pattern classification algorithms based on ACO-SVM

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
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  2. 2
    Hybrid ACO and SVM algorithm for pattern classification

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…This is achieved by performing the SVM parameters’ tuning and feature subset selection processes simultaneously. Hybridization algorithms between ACO and SVM techniques were proposed. …”
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  3. 3
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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    Final Year Project
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  4. 4
    Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification

    Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification by Prathama, Y.B.H., Shapiai, M.I., Aris, S.A.M., Ibrahim, Z., Jaafar, J., Fauzi, H.

    Published 2017
    “…In this paper, we propose an algorithm called Feature Scaling Common Spatial Pattern (FSc-CSP) to overcome the problem of feature selection. …”
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  5. 5
    Swarm negative selection algorithm for electroencephalogram signals classification

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…Such automated systems must rely on robust and effective algorithms for detection and prediction. Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. …”
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  6. 6
    Naive Bayes-guided bat algorithm for feature selection

    Naive Bayes-guided bat algorithm for feature selection by Taha A.M., Mustapha A., Chen S.-D.

    Published 2023
    “…The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. …”
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  7. 7
    Design of intelligent Qira’at identification algorithm

    Design of intelligent Qira’at identification algorithm by Kamarudin, Noraziahtulhidayu

    Published 2017
    “…The process of the SPAP Algorithm is to extend parameters of the Affine Projection Block with two different selections of windowing length that affect the final accuracy on pattern classification. …”
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  8. 8
    Routing performance enhancement in hierarchical torus network by link-selection algorithm

    Routing performance enhancement in hierarchical torus network by link-selection algorithm by Rahman, M.M. Hafizur, Horiguchi, Susumu

    Published 2005
    “…In this paper, we propose a link-selection algorithm for efficient use of physical links of the HTN, while keeping the link-selection algorithm as simple as the dimension-order routing algorithm. …”
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  9. 9
    Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability

    Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability by Romli, Nurul Atiqah

    Published 2024
    “…A Binary Clonal Selection Algorithm is being proposed to ensure optimal generation of the superior final neuron states. …”
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  10. 10
    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection

    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2020
    “…This paper proposes a competitive grey wolf optimizer (CGWO) to solve the feature selection problem in electromyography (EMG) pattern recognition. …”
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  11. 11
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In comparison to different single algorithms for feature selection,experimental results show that the proposed ensemble method is able to reduce dimensionality, the number of irrelevant features and produce reasonable classifier accuracy. …”
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  12. 12
    Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification

    Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification by Nisar, Humaira, Malik, Aamir Saeed, Choi, Tae-Sun

    Published 2012
    “…This is the basis of the proposed algorithm. The proposed algorithm involves a multistage approach that includes motion vector prediction and motion classification using the characteristics of video sequences. …”
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  13. 13
    The non-uniform communication performance of adaptive routing for hierarchical interconnection network for 3D VLSI

    The non-uniform communication performance of adaptive routing for hierarchical interconnection network for 3D VLSI by Miura, Yasuyuki, Watanabe, Shigeyoshi, Rahman, M.M. Hafizur

    Published 2015
    “…Thus, those algorithms can also be applied to TESH network. We have proposed three adaptive routing algorithms - channel-selection, link-selection, and dynamic dimension reversal - for the efficient use of network resources of a TESH network to improve dynamic communication performance. …”
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  14. 14
    Finger Vein Recognition Using Pattern Map As Feature Extraction

    Finger Vein Recognition Using Pattern Map As Feature Extraction by Teoh, Saw Beng

    Published 2012
    “…Experimental results show that the proposed pattern map algorithm has better performance with a consistent identification rate of 99% and above compared to existing methods such as PCA and Gabor with FVCode. …”
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  15. 15
    Dynamic communication performance enhancement in hierarchical torus network by selection algorithm

    Dynamic communication performance enhancement in hierarchical torus network by selection algorithm by Rahman, M.M. Hafizur, Sato, Yukinori, Inoguchi, Yasushi

    Published 2012
    “…The dynamic communication performances of an HTN is evaluated by using dimension-order routing and proposed adaptive routing algorithms under various traffic patterns. …”
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  16. 16
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  17. 17
    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…Experimental results of the EBGWO algorithm on the NSL-KDD dataset in terms of number of selected features and classification accuracy are superior to other benchmark optimisation algorithms. …”
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  18. 18
    A partition based feature selection approach for mixed data clustering / Ashish Dutt

    A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

    Published 2020
    “…The proposed approach exploits the pre-processing nature of the partition clustering algorithm in the selection of weight assignment for nominal features. …”
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  19. 19
    Dynamic communication performance enhancement in Hierarchical Torus Network by selection algorithm

    Dynamic communication performance enhancement in Hierarchical Torus Network by selection algorithm by Rahman, M.M. Hafizur, Sato, Yukinori, Inoguchi, Yasushi

    Published 2010
    “…The dynamic communication performances of an HTN is evaluated by using dimension-order routing and proposed adaptive routing algorithms under various traffic patterns. …”
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    Proceeding Paper
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  20. 20
    Application of the bees algorithm to the selection features for manufacturing data

    Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

    Published 2007
    “…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
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