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  1. 1
    Performance evaluation of real-time multiprocessor scheduling algorithms

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…The aim of this evolution is to reflect the unseen time overhead incurred by optimal real-time algorithm, represented by LRE-TL, which might hinder the claimed optimality of such algorithms when they are practically implemented. …”
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  2. 2
    Development of Simulated Annealing Based Scheduling Algorithm for Two Machines Flow Shop Problem

    Development of Simulated Annealing Based Scheduling Algorithm for Two Machines Flow Shop Problem by M., Muziana, Kamal Z., Zamli

    Published 2015
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  3. 3
    Machine learning: tasks, modern day applications and challenges

    Machine learning: tasks, modern day applications and challenges by Aljuaid, Lamyaa Zaed, Koh, Tieng Wei, Sharif, Khaironi Yatim

    Published 2019
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  4. 4
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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    Thesis
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  5. 5
    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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  6. 6
    Development of a mathematical model for the prediction of chip formation instability and its verification by fuzzy logic with genetic algorithm

    Development of a mathematical model for the prediction of chip formation instability and its verification by fuzzy logic with genetic algorithm by Ullah Patwari, Mohammed Anayet, Amin, A. K. M. Nurul, Istihyaq , M.H., Faris, Waleed Fekry

    Published 2010
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  7. 7
    Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China

    Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

    Published 2024
    “…In this study, different supervised and unsupervised machine learning algorithms are proposed: artificial neural network (ANN), AutoRegressive Integrated Moving Aveage (ARIMA) and support vector machine (SVM). …”
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  8. 8
    Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data

    Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data by Ong, Song Quan, Pradeep Isawasan, Ahmad Mohiddin Mohd Ngesom, Hanipah Shahar, As’malia Md Lasim, Gomesh Nair

    Published 2023
    “…Machine learning algorithms (ML) are receiving a lot of attention in the development of predictive models for monitoring dengue transmission rates. …”
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  9. 9
    Phishing attack detection using machine learning method

    Phishing attack detection using machine learning method by Jupin, John Arthur

    Published 2019
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  10. 10
    Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.]

    Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.] by Mohd Fuzi, Mohd Faris, Mohd Shahirudin, Syamir, Abd Halim, Iman Hazwam, Jamaluddin, Muhammad Nabil Fikri

    Published 2023
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  11. 11
    New Approach for E-Commerce Stock Prices Prediction : Combination of Machine Learning and Technical Analysis

    New Approach for E-Commerce Stock Prices Prediction : Combination of Machine Learning and Technical Analysis by Kelvin Lee, Yong Ming, Mohamad, Jais, Pick Soon, Lee

    Published 2022
    “…The investors are recommended to use machine learning algorithms to predict the price movements of e-commerce stocks. …”
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  12. 12
    Machine learning approach of predicting Airline flight delay using Naïve Bayes Algorithm / Ahmad Adib Baihaqi Shukri ... [et al.]

    Machine learning approach of predicting Airline flight delay using Naïve Bayes Algorithm / Ahmad Adib Baihaqi Shukri ... [et al.] by Shukri, Ahmad Adib Baihaqi, Mohamed Yusoff, Syarifah Adilah, Warris, Saiful Nizam, Abu Bakar, Mohd Saifulnizam, Kadar, Rozita

    Published 2024
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  13. 13
    Waste management using machine learning and deep learning algorithms

    Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

    Published 2020
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  14. 14
    Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables

    Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables by Che Dom, Nazri, Mohd Hardy Abdullah, Nur Athen, Dapari, Rahmat, Salleh, Siti Aekbal

    Published 2025
    “…However, current models often rely on coarse regional data and fail to account for microclimatic variations, limiting their predictive accuracy in dengue hotspots. This study developed fine-scale predictive models using machine learning algorithms; Artificial Neural Networks (ANN), Random Forest (RF), and Support Vector Machines (SVM) to estimate mosquito abundance and dengue risk at the species level based on daily microclimatic data (temperature, relative humidity, and rainfall) collected over 26 weeks in Kuala Selangor, Malaysia. …”
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  15. 15
    The influence of machine learning on the predictive performance of cross-project defect prediction: empirical analysis

    The influence of machine learning on the predictive performance of cross-project defect prediction: empirical analysis by Bala, Yahaya Zakariyau, Samat, Pathiah Abdul, Sharif, Khaironi Yatim, Manshor, Noridayu

    Published 2024
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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
    Forest mapping in Peninsular Malaysia using Random Forest and Support Vector Machine Classifiers on Google Earth Engine

    Forest mapping in Peninsular Malaysia using Random Forest and Support Vector Machine Classifiers on Google Earth Engine by Farah Nuralissa Muhammad, Lam, Kuok Choy

    Published 2023
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  18. 18
    The Determinant Factors for the Issuance of Central Bank Digital Currency (CBDC) in Malaysia using Machine Learning Framework

    The Determinant Factors for the Issuance of Central Bank Digital Currency (CBDC) in Malaysia using Machine Learning Framework by Normi Sham Awang, Abu Bakar, Norzariyah, Yahya, Norbik Bashah, Idris, Engku Rabiah Adawiah, Engku Ali, Jasni, Mohamad Zain, Erni Eliana, Khairuddin, Ahmad Firdaus, Zainal Abidin, Murtaj, Sheikh Mohammad Tahsin, Siti Sarah, Maidin

    Published 2024
    “…The overall CentralBank Digital Currency Project Index (CBDCPI) was selected as a target variable,while two machine learning algorithms, Random Forest and XGBoost were utilized to identify the determining variables. …”
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  19. 19
    GIS-based air quality modelling: spatial prediction of PM10 for Selangor State, Malaysia using machine learning algorithms

    GIS-based air quality modelling: spatial prediction of PM10 for Selangor State, Malaysia using machine learning algorithms by Tella, A., Balogun, A.-L.

    Published 2021
    “…Although some studies have predicted air pollutants such as particulate matter (PM) using machine learning algorithms (MLAs), there is a paucity of studies on spatial hazard assessment with respect to the air quality index (AQI). …”
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  20. 20
    Anomaly detection in network traffic using machine learning

    Anomaly detection in network traffic using machine learning by Amir Muhammad Hafiz, Othman, Mohd Faizal, Ab Razak, Mohd Izham, Mohd Jaya, Nurul Azma, Abdullah, Alanda, Alde

    Published 2026
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