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  1. 1
    A Proposed False Report Identification Algorithm for a Mobile Application in the IoT Environment

    A Proposed False Report Identification Algorithm for a Mobile Application in the IoT Environment by Rajoo, S, Magalingam, P, Idris, NB, Samy, GN, Maarop, N, Shanmugam, B, Perumal, S

    Published 2024
    Proceedings Paper
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  2. 2
    Integrated ACOR/IACOMV-R-SVM Algorithm

    Integrated ACOR/IACOMV-R-SVM Algorithm by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2017
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  3. 3
    An improved framework for content and link-based web spam detection: a combined approach

    An improved framework for content and link-based web spam detection: a combined approach by Shahzad, Asim

    Published 2021
    “…The content-based web spam detection framework uses three proposed and two improved content-based algorithms for web spam detection. …”
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    Thesis
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  4. 4
    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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  5. 5
    A Knowledge Management System for Assessing Lecturer Competence in Indonesian Higher Educational Institutions

    A Knowledge Management System for Assessing Lecturer Competence in Indonesian Higher Educational Institutions by Syaripudin, Undang

    Published 2025
    “…Lecturer competency measurement is carried out by first checking employee status using the SVM algorithm with an accuracy value of 72.28%, then using a hybrid SVM and PSO algorithm with an accuracy value of 100%. …”
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  6. 6
    Intelligent classification algorithms in enhancing the performance of support vector machine

    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2019
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  7. 7
    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier

    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
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  8. 8
    A WEB-BASED SYSTEM FOR THE PREDICTION OF STUDENT PERFORMANCE IN UPCOMING PUBLIC EXAMS BASED ON ACADEMIC RECORDS

    A WEB-BASED SYSTEM FOR THE PREDICTION OF STUDENT PERFORMANCE IN UPCOMING PUBLIC EXAMS BASED ON ACADEMIC RECORDS by DELLON, NELSON BRUNNIE

    Published 2023
    “…Teachers will be able to precisely forecast their students' impending grades utilizing the system's web-based application integration and machine learning algorithms. …”
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    Final Year Project Report / IMRAD
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  9. 9
    Classifying good and bad websites

    Classifying good and bad websites by Koo, Ee Woon

    Published 2015
    “…Websites classification has become a vital subject matter as most websites are increasingly being used as a platform for various applications. These web pages often contain semi-structured content which make the classification process challenging. …”
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  10. 10
    Using the bees algorithm to optimise a support vector machine for wood defect classification

    Using the bees algorithm to optimise a support vector machine for wood defect classification by Pham, D.T, Muhammad, Zaidi, Mahmuddin, Massudi, Ghanbarzadeh, Afshin, Koc, Ebubekir, Otri, Sameh

    Published 2007
    “…This paper describes a new application of the Bees Algorithm to the optimization of a Support Vector Machine (SVM) for the problem of classifying defects in plywood. …”
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  11. 11
    Detection and classification of conflict flows in SDN using machine learning algorithms

    Detection and classification of conflict flows in SDN using machine learning algorithms by Mutaz Hamed Hussien Khairi, Sharifah Hafizah Syed Ariffin, Nurul Mu'azzah Abdul Latiff, Kamaludin Mohamad Yusof, Mohamed Khalafalla Hassan, Fahad Taha Al-Dhief, Mosab Hamda, Suleman Khan, Muzaffar Hamzah

    Published 2021
    “…The EFDT and hybrid DT-SVM algorithms were designed and deployed based on DT and SVM algorithms to achieve improved performance. …”
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  12. 12
    Solving SVM model selection problem using ACOR and IACOR

    Solving SVM model selection problem using ACOR and IACOR by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
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  13. 13
    Malware visualizer: A web apps malware family classification with machine learning

    Malware visualizer: A web apps malware family classification with machine learning by Mohd Zamri, Osman, Ahmad Firdaus, Zainal Abidin, Rahiwan Nazar, Romli

    Published 2021
    “…This project uses three classification algorithm which are Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN). …”
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  14. 14
    An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system

    An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system by M. W., Mustafa, H., Shareef, M. H., Sulaiman, S. N., Abd. Khalid, S. R., Abd. Rahim, Omar, Aliman

    Published 2011
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  15. 15
    Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters

    Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters by Teguh, Sutanto, Muhammad Rafli, Aditya, Haldi, Budiman, M.Rezqy, Noor Ridha, Usman, Syapotro, Noor, Azijah

    Published 2024
    “…This research provides new insights into the application of machine learning algorithms for water quality management as well as guidance for optimal algorithm selection.…”
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  16. 16
    Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm

    Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

    Published 2021
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  17. 17
    Support Vector Machines (SVM) in Test Extraction

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

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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    Final Year Project
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  18. 18
    Support Vector Machines (SVM) in Test Extraction

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

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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    Final Year Project
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  19. 19
    VEHICLE CLASSIFICATION FROM CCTV IMAGES AND VIDEOS

    VEHICLE CLASSIFICATION FROM CCTV IMAGES AND VIDEOS by KAMARUDDIN, ERNA SHAFFIQA

    Published 2018
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  20. 20
    A malicious URLs detection system using optimization and machine learning classifiers

    A malicious URLs detection system using optimization and machine learning classifiers by Lee, Ong Vienna, Heryanto, Ahmad, Mohd Faizal, Ab Razak, Anis Farihan, Mat Raffei, Eh Phon, Danakorn Nincarean, Shahreen, Kasim, Sutikno, Tole

    Published 2020
    “…In this study, we applied features optimization approaches by using a bio-inspired algorithm for selecting significant URL features which able to detect malicious URLs applications. …”
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