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  1. 1
    A new ant based rule extraction algorithm for web classification

    A new ant based rule extraction algorithm for web classification by Ku-Mahamud, Ku Ruhana, Saian, Rizauddin

    Published 2011
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  2. 2
    Comparison of attribute selection methods for web texts categorization

    Comparison of attribute selection methods for web texts categorization by Saian, Rizauddin, Ku-Mahamud, Ku Ruhana

    Published 2010
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  3. 3
    A new variant of black hole algorithm based on multi population and levy flight for clustering problem

    A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

    Published 2020
    “…In keeping with this limitation, this study proposes a new variant of BH through two different modifications on the original BH. The first modification is the integration of BH algorithm and levy flight, which result in data clustering method, namely “Levy Flight Black Hole (LBH)”. …”
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  4. 4
    An improved ACS algorithm for data clustering

    An improved ACS algorithm for data clustering by Mohammed Jabbar, Ayad, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2020
    “…Comparison of the performance of several common clustering algorithms using real-world datasets shows that the accuracy results of the proposed algorithm surpasses other algorithms.…”
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  5. 5
    Balancing exploration and exploitation in ACS algorithms for data clustering

    Balancing exploration and exploitation in ACS algorithms for data clustering by Jabbar, Ayad Mohammed, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…The performance of the proposed algorithm is compared with that of several common clustering algorithms using real-world datasets. …”
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  6. 6
    Extensions to the K-AMH algorithm for numerical clustering

    Extensions to the K-AMH algorithm for numerical clustering by Seman, Ali, Mohd Sapawi, Azizian

    Published 2018
    “…It can also be used to cluster numerical values with minimum modification to the original algorithm. …”
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  7. 7
    Detection of multiple outliners in linear regression using nonparametric methods

    Detection of multiple outliners in linear regression using nonparametric methods by Adnan, Robiah

    Published 2004
    “…Generally, method proposed by Sebert et al. (1998) is based on the use of single linkage clustering algorithm with the Euclidean distances to cluster the points in the plots of standard predicted versus residuals values from a linear regression model. …”
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  8. 8
    An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets

    An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets by Azlin, Ahmad, Rubiyah, Yusof, Nor Saradatul Akmar, Zulkifli, Mohd Najib, Ismail

    Published 2021
    “…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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  9. 9
    An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets

    An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets by Ahmad, Azlin, Yusof, Rubiyah, Zulkifli, Nor Saradatul Akma, Ismail, Mohd Najib

    Published 2021
    “…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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  10. 10
    Identifying multiple outliers in linear regression : Robust fit and clustering approach

    Identifying multiple outliers in linear regression : Robust fit and clustering approach by Adnan, Robiah, Setan, Halim, Mohammad, Mohd. Nor

    Published 2001
    “…This research provides a clustering based approach for determining potential candidates for outliers.This is a modification of the method proposed by Serbert et.al (1998).It is based on using the single linkage clustering algorithm to group the standardized predicted and residual values of data set fit by least trimmed of squares (LTS).…”
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  11. 11
    Kernel and multi-class classifiers for multi-floor wlan localisation

    Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

    Published 2016
    “…For floor localisation, the strategy is based on developing the algorithm to determine the floor by utilising fingerprint clustering technique. …”
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  12. 12
    Task scheduling in cloud computing using hybrid genetic algorithm and bald eagle search (GA-BES)

    Task scheduling in cloud computing using hybrid genetic algorithm and bald eagle search (GA-BES) by Kamal Khairi Supaprhman

    Published 2022
    “…As for the running method the compilation of the code will be run by using cmd and Ant Apache and the total average result of 30 simulation will be view on the web base application will be run using xampp.…”
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  13. 13
    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm

    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm by Muhammad Syahril Mohamad Sainal

    Published 2022
    “…Furthermore, CloudSim simulator will be used to evaluate the performance of this algorithm. The result of the algorithm performance will be appeared in web application system. …”
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  14. 14
    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat

    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

    Published 2021
    “…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
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  15. 15
    Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing

    Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing by Elrasheed Ismail, Sultan

    Published 2013
    “…Cloud Computing systems are widely applied in many fields such as communication data management, web application, network monitoring, financial management and so on. …”
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  16. 16
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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  17. 17
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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  18. 18
    An Iterated Two-Step Sinusoidal Pitch Contour Formulation for Expressive Speech Synthesis

    An Iterated Two-Step Sinusoidal Pitch Contour Formulation for Expressive Speech Synthesis by Ramli, Izzad, Jamil, Nursuriati, Seman, Noraini

    Published 2021
    “…All the shapes of pitch contours from STORY_DATA were analyzed and clustered into the standard six main pitch contour clusters for storytelling. …”
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  19. 19
    Instance matching framework for heterogeneous semantic web content over linked data environment

    Instance matching framework for heterogeneous semantic web content over linked data environment by Mansir, Abubakar

    Published 2021
    “…The output of each algorithm is evaluated, the results have shown that each algorithm performs well and outperforms the existing algorithms on all test cases in terms better output generation and effective handling of heterogeneity from different domains, which is a necessary concern in all data-intensive problems. …”
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  20. 20
    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images

    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

    Published 2024
    “…The second segmentation algorithm combines Delaunay triangulation clustering in the spatial domain and Particle Swarm Optimization (PSO). …”
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