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  1. 1
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  2. 2
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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  3. 3
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
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  4. 4
    On randomness of compressed data using non-parametric randomness tests

    On randomness of compressed data using non-parametric randomness tests by Al-Khayyat, Kamal A., Alshaikhli, Imad Fakhri Taha, Vijayakumar, V.

    Published 2018
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  5. 5
    Fsm-Based Enhanced March C- Algorithm For Memory Built-In Self-Test

    Fsm-Based Enhanced March C- Algorithm For Memory Built-In Self-Test by CH’NG , MING ZONG

    Published 2017
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  6. 6
    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation

    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

    Published 2018
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  7. 7
    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection

    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

    Published 2015
    “…However the average classification accuracy of 84.74% on the unseen test data did not achieve the acceptable average success rate of 90% in this application. …”
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  8. 8
    ANALYSIS AND INTERPRETATION OF PRESSURE TRANSIENT TEST DATA BY RECENT ROBUST DECONVOLUTION METHODS

    ANALYSIS AND INTERPRETATION OF PRESSURE TRANSIENT TEST DATA BY RECENT ROBUST DECONVOLUTION METHODS by Mohd Mustafa, Muhammad Izzatullah

    Published 2013
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  9. 9
    Fault detection with optimum March test algorithm

    Fault detection with optimum March test algorithm by Zakaria, Nor Azura, Wan Hassan, Wan Zuha, Abdul Halin, Izhal, Mohd Sidek, Roslina, Xiao, Qing Wen

    Published 2013
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  10. 10
    Randomness Tests On Nine Data Categories Of RECTANGLE Using NIST Statistical Test Suite

    Randomness Tests On Nine Data Categories Of RECTANGLE Using NIST Statistical Test Suite by Abdul Alif Zakaria, Nur Hafiza Zakaria, Maslina Daud, Azni Hazlizan Ab Halim, Farida Hazwani Mohd Ridzuan

    Published 2024
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  11. 11
    Diabetes prediction system using clonal selection algorithm / Nor Aishah Mustapa

    Diabetes prediction system using clonal selection algorithm / Nor Aishah Mustapa by Mustapa, Nor Aishah

    Published 2012
    “…The data included in the system is a tested and accurate data. …”
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  12. 12
    Parallelization of noise reduction algorithm for seismic data on a beowulf cluster

    Parallelization of noise reduction algorithm for seismic data on a beowulf cluster by Aziz, I. A., Sandran, T., Haron, N. S., Hasan, M. H, Mehat, M.

    Published 2010
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  13. 13
    Steganography algorithm to hide secret message inside an image

    Steganography algorithm to hide secret message inside an image by Ibrahim, Rosziati, Teoh, Suk Kuan

    Published 2011
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  14. 14
    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm

    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm by Ali, M., Jung, L.T., Abdel-Aty, A.-H., Abubakar, M.Y., Elhoseny, M., Ali, I.

    Published 2020
    “…The k-NN algorithm is one of the most renowned ML algorithms widely used in the area of data classification research. …”
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  15. 15
    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm

    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm by Ali, M., Jung, L.T., Abdel-Aty, A.-H., Abubakar, M.Y., Elhoseny, M., Ali, I.

    Published 2020
    “…The k-NN algorithm is one of the most renowned ML algorithms widely used in the area of data classification research. …”
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  16. 16
    Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing

    Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing by Goh, Kwang Yi

    Published 2023
    “…We enhanced the Q-Learning algorithm for action selection based on potential action abilities and proposed a tool, namely CrashDroid, that allows the automation of testing context-aware Android applications. …”
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  17. 17
    Reduced Galloping Column Algorithm For Memory Testing

    Reduced Galloping Column Algorithm For Memory Testing by Ngieng , Siew Ching

    Published 2015
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  18. 18
    Analysis and Modification of Grain - 128 Stream Cipher Algorithm

    Analysis and Modification of Grain - 128 Stream Cipher Algorithm by Norul Hidayah Lot@Ahmad Zawawi

    Published 2024
    thesis::master thesis
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  19. 19
    Pairwise Test Data Generation based on Flower Pollination Algorithm

    Pairwise Test Data Generation based on Flower Pollination Algorithm by Nasser, Abdullah B., Alsewari, Abdulrahman A., Tairan, Nasser M., Kamal Z., Zamli

    Published 2017
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  20. 20
    Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting

    Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting by Ali, Noor Rasidah, Ku Mahamud, Ku Ruhana

    Published 2017
    “…The performance of the clustering algorithm gets even worse if it relies on actual data and many clustering algorithms are often faced with conflict in handling high dimensional data. …”
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