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    An energy efficient reinforcement learning based cooperative channel sensing for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, Sali, Aduwati, A. Rasid, Mohd Fadlee, Mohamad, Hafizal

    Published 2017
    “…Simulation results show convergence and adaptability of the algorithm to dynamic environment in achieving optimal solutions. …”
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    Article
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    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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    Conference or Workshop Item
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    A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network by Mustapha, Ibrahim

    Published 2016
    “…Simulation results show convergence, learning and adaptability of the RL based algorithms to dynamic environment toward achieving the optimal solutions. …”
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    Thesis
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    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
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    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

    Published 2019
    “…In the simulation the robot is equipped with thirteen distance sensing sensors. From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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    Thesis
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    Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data by Terence Chia Yi Kai, Agus Saptoro, Zulfan Adi Putra, King Hann Lim, Wan Sieng Yeo, Jaka Sunarso

    Published 2025
    “…Current FDD technologies mostly rely on data-driven solutions by making full use of abundant process data collected by the state-of-the-art distributed process instruments and sensors. Deep learning algorithms were widely used among all the data-driven algorithms. …”
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    Article
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    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
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    Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2022
    “…There were also attempts to hybridize SKF with other famous algorithms such as Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Sine Cosine Algorithm (SCA) to improve its performance. …”
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    Conference or Workshop Item
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    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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    Thesis
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    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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    Thesis
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    Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

    Published 2006
    “…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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    Thesis
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    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

    Published 2009
    “…We then consider the task of determining near globally optimal solutions of discrete-valued optimal control problems. …”
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    Thesis
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