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  1. 1
    Load Balancing Using The Consensus Control Algorithm For A Network Server System

    Load Balancing Using The Consensus Control Algorithm For A Network Server System by Loon, Alan Tan Chin

    Published 2016
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  2. 2
    A Review on Attack Graph Analysis for IoT Vulnerability Assessment: Challenges, Open Issues, and Future Directions

    A Review on Attack Graph Analysis for IoT Vulnerability Assessment: Challenges, Open Issues, and Future Directions by Almazrouei O.S.M.B.H., Magalingam P., Hasan M.K., Shanmugam M.

    Published 2024
    “…Attack graphs serve as a valuable cybersecurity tool for modeling and analyzing potential attack scenarios on systems, networks, or applications. …”
    Review
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  3. 3
    An optimal approximation algorithm for optimization of un-weighted minimum vertex cover problem

    An optimal approximation algorithm for optimization of un-weighted minimum vertex cover problem by Fayaz, Muhammad, Arshad, S, Shah, Abdul Salam, Shah, Asadullah

    Published 2016
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  4. 4
    The application of suitable sports games for junior high school students based on deep learning and artificial intelligence

    The application of suitable sports games for junior high school students based on deep learning and artificial intelligence by Ji, Xueyan, Samsudin, Shamsulariffin, Hassan, Muhammad Zarif, Farizan, Noor Hamzani, Yuan, Yubin, Chen, Wang

    Published 2025
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  5. 5
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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  6. 6
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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  7. 7
    Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem

    Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem by Fayaz, Muhammad, Arshad,, Shakeel, Shah,, Abdul Salam, Shah, Asadullah

    Published 2018
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  8. 8
    Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems

    Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems by Rahimi, Amir Masoud, Ramezani-Khansari, Ehsan

    Published 2021
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  9. 9
    Artificial Bee Colony Algorithm for Pairwise Test Generation

    Artificial Bee Colony Algorithm for Pairwise Test Generation by Alazzawi, Ammar K., Homaid, Ameen A. Ba, Alomoush, Alaa A., Alsewari, Abdulrahman A.

    Published 2017
    “…PABC progresses as a means to achieve the effective use of the artificial bee colony algorithm for pairwise testing reduction.…”
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  10. 10
    A hybrid P-graph and WEKA approach in decision-making: waste conversion technologies selection

    A hybrid P-graph and WEKA approach in decision-making: waste conversion technologies selection by Ali, Rabiatul Adawiyah, Nik Ibrahim, Nik Nor Liyana, Wan Abdul Karim Ghani, Wan Azlina, Sani, Nor Samsiah, Hon, Loong Lam

    Published 2022
    “…The mean absolute error and root mean square error are 0.0042 and 0.0354. …”
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  11. 11
    A Single Objective Flower Pollination Algorithm for Modeling the Horizontal Flexible Plate System

    A Single Objective Flower Pollination Algorithm for Modeling the Horizontal Flexible Plate System by Siti Zakiah, Maseri, Muhamad Sukri, Hadi, Annisa, Jamali, Hanim, Mohd Yatim, Mat Hussin, Ab Talib, Intan Zaurah, Mat Darus

    Published 2020
    “…The gained model in this simulation is approved utilizing the most minimal mean squared error, correlation tests, and pole zero graph stability due to check the robustness of the model. …”
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  12. 12
    Robust overlapping community detection in complex networks with graph convolutional networks and fuzzy C-means

    Robust overlapping community detection in complex networks with graph convolutional networks and fuzzy C-means by Mohammed Al-Andoli, Mohammed Nasser, Che Ku Mohd, Che Ku Nuraini, Harny, Irianto, Jamil Alsayaydeh, Jamil Abedalrahim, Alwayle, Ibrahim M., Ahmed Abuhoureyah, Fahd Saad

    Published 2024
    “…In this paper, we propose an efficient method called GCNFCM, which utilizes Graph Convolutional Networks (GCNs), Fuzzy C-means (FCM), and the modularity Q algorithm for overlapping community detection. …”
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  13. 13
    The conceptual framework of knowledge of large scale and incomplete graphs of skyline queries optimization using machine learning

    The conceptual framework of knowledge of large scale and incomplete graphs of skyline queries optimization using machine learning by Noor, Ubair, Hassan, Raini, Dwi Handayani, Dini Oktarina

    Published 2025
    “…The preliminary results using the K means Clustering Algorithm showed that the conceptual framework successfully grouped similar data points, facilitating the identification of skyline points. …”
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  14. 14
    Generic DNA encoding design scheme to solve combinatorial problems

    Generic DNA encoding design scheme to solve combinatorial problems by Rofilde, Hasudungan

    Published 2015
    “…The complexity of combinatorial problems is classified as NP meaning that algorithms are yet to exist to efficiently solve the problem. …”
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  15. 15
    A Hybrid Approach For Web Search Result Clustering Based On Genetic Algorithm With K-means

    A Hybrid Approach For Web Search Result Clustering Based On Genetic Algorithm With K-means by Norita Md Norwawi, Bourair Al-attar, Ahmed J. Allami, Ali Thoulfikar A. Imeer, Yusor Fadhil Alasadi, Hawraa M. Kadhim

    Published 2024
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  16. 16
    Automated Validation of Crowdsourced Data

    Automated Validation of Crowdsourced Data by Ibrahim Z., Aris H., Mansur A.

    Published 2023
    Conference Paper
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  17. 17
    Technical report: an application of graph theory in place a sensor at traffic light / Nur Shamimi Saleh Huddin, Nurul Nadiah Abd Ghani and Wan Nur Hafawati Wan Hassan

    Technical report: an application of graph theory in place a sensor at traffic light / Nur Shamimi Saleh Huddin, Nurul Nadiah Abd Ghani and Wan Nur Hafawati Wan Hassan by Saleh Huddin, Nur Shamimi, Abd Ghani, Nurul Nadiah, Wan Hassan, Wan Nur Hafawati

    Published 2016
    “…In this study, the basic application of Graph Theory for Traffic Control is used to develop the compatibility graph, find the minimal edge set and draw the connectivity graph. …”
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  18. 18
    A New Unsupervised Validation Index Model Suitable for Energy-Efficient Clustering Techniques in VANET

    A New Unsupervised Validation Index Model Suitable for Energy-Efficient Clustering Techniques in VANET by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L.

    Published 2024
    “…These cluster validation indexes focus on the internal or external cluster similarity, and some of them deal with both cases. The employing of graph-based distance to non-spherical clusters and selection of reference points will not be effective all the time because the average distance between reference points and all nodes will be changed dynamically such as in the VANET application. …”
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  19. 19
    Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking

    Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking by Boroujeni, Farsad Zamani

    Published 2012
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  20. 20
    Combined generative adversarial network and fuzzy C-means clustering for multi-class voice disorder detection with an imbalanced dataset

    Combined generative adversarial network and fuzzy C-means clustering for multi-class voice disorder detection with an imbalanced dataset by Chui, K.T., Lytras, M.D., Vasant, P.

    Published 2020
    “…An automatic diagnosis for voice disorders via machine learning algorithms is desired to reduce the cost and time needed for examination by doctors and speech-language pathologists. …”
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