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  1. 1

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

    Published 2016
    “…The CPU profiler of JavaTM VisualVM measures the number of invocations of scheduling event handlers (procedures) in each algorithm as well as the total time spent in all invocations of this handler. …”
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    Conference or Workshop Item
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    A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

    Published 2014
    “…In this type of environment it is nearly impossible to prove the effectiveness of a scheduling algorithm. Hence the main objective of this study is to develop a desktop grid simulator toolkit for measuring and modeling scheduler algorithm performance. …”
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    Final Year Project
  4. 4

    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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    Thesis
  5. 5

    Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

    Published 2006
    “…This paper reports the power fill techniques using GA in scheduling. Class timetabling problem is one of the applications in scheduling. …”
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    Thesis
  6. 6

    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
    “…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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    Thesis
  7. 7

    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

    Published 2005
    “…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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    Thesis
  8. 8

    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

    Published 2024
    “…This study recommends a selection trade-off as the function of prediction efficiency and efficacy of the algorithm. Particularly, the proposed optimized Bagged Trees are the most effective algorithm for energy demand prediction applications, and the proposed optimized Medium Trees are the most efficient algorithm for real-time systems. …”
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    Thesis
  9. 9

    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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    Article
  10. 10

    Decision tree-based approach for online management of PEM fuel cells for residential application by Mohd Rusllim, Mohamed

    Published 2004
    “…In this research, a Decision Tree (DT) algorithm is employed to obtain the optimal, or quasioptimal, settings of the fuel cell online and in a general framework. …”
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    Thesis
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    Batch mode heuristic approaches for efficient task scheduling in grid computing system by Maipan-Uku, Jamilu Yahaya

    Published 2016
    “…Many algorithms have been implemented to solve the grid scheduling problem. …”
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    Thesis
  13. 13

    Decision tree-based approach for online management of pem fuel cells for residential application by Mohamed, Mohd Rusllim

    Published 2004
    “…In this research, a Decision Tree (DT) algorithm was employed to obtain the optimal, or quasi-optimal, settings of the fuel cell online and in a general framework. …”
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    Thesis
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    Smart student timetable planner by Wong, Xin Tong

    Published 2025
    “…Course data is managed in CSV format, parsed into JSON for fast processing, while sessionStorage and localStorage handle user data within active sessions. A Genetic Algorithm forms the core scheduling engine, generating optimized timetables that respect both hard constraints, such as avoiding clashes, and soft constraints, such as personal preferences.The final output of this project is a functional web-based timetable planner that successfully enhances scheduling efficiency, reduces the likelihood of errors, and improves the overall academic planning experience. …”
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    Final Year Project / Dissertation / Thesis
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    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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    Thesis
  17. 17

    Cyberbullying detection: a machine learning approach by Yeong, Su Yen

    Published 2022
    “…The machine learning algorithm, Support Vector Machine was chosen after comparing it with other algorithms such as Multinomial Naïve Bayes, Decision Tree Classifier, and Random Forest Classifier. …”
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    Final Year Project / Dissertation / Thesis
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    Driver behaviour classification: a research using OBD-II data and machine learning by Muhamad Fadzil, Nur Farisya Aqilah, Mohd Fadzir, Hilda, Mansor, Hafizah, Rahardja, Untung

    Published 2024
    “…The relationship between all features and engine speed is analysed to select the optimal features, which include engine speed, vehicle speed, throttle position, and calculated engine load. Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
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    Article
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    Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Kamarulzaman, Kamarudin, Mohd Aminudin, Jamlos

    Published 2022
    “…A PLS regression is used on NIR spectra to implement the prediction of ergosterol concentration which shows good corelation of R = 0.861 between the ergosterol concentration and oil palm NIR spectra. Four different ML algorithms are tested for prediction of G. boninense infection: K-Nearest Neighbour (kNN), Naïve Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT) are tested which depicted DT algorithm achieves a satisfactory overall performance with high accuracy up to 93.1% and F1-score of 92.6% compared to other algorithms. …”
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    Article