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  1. 1
    An energy efficient reinforcement learning based cooperative channel sensing for cognitive radio sensor networks

    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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  2. 2
    Maximum 2-satisfiability in radial basis function neural network

    Maximum 2-satisfiability in radial basis function neural network by Shehab Abdulhabib Alzaeemi, Saratha Sathasivam, Mohd Shareduwan Mohd Kasihmuddin, Mohd. Asyraf Mansor

    Published 2020
    “…This paper presents a new paradigm in using MAX2SAT by implementing in Radial Basis Function Neural Network (RBFNN). …”
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  3. 3
    Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin

    Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin by Alsahag, Ali Mohammed, Mohd Ali, Borhanuddin, Noordin, Nor Kamariah, Mohamad, Hafizal

    Published 2014
    “…In this paper, an efficient bandwidth allocation algorithm for the uplink traffic in mobile WiMAX is proposed. …”
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  4. 4
    A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network

    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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  5. 5
    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm

    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

    Published 2018
    “…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. This is to remedy the problem of using the existing Min-Max (MM) and Decimal Scaling (DS) techniques, which have overflow weakness. …”
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  6. 6
    Effective downlink resource management for wimax networks

    Effective downlink resource management for wimax networks by Shareef, Zayd Ashraf Najeeb

    Published 2018
    “…Our EDRM framework involves three functions: Class-Based Scheduling (CBS) algorithm, Dynamic Bandwidth Allocation (DBA) scheme and Link Session Management (LSM) policy. …”
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  7. 7
    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof

    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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  8. 8
    Modern fuzzy min max neural networks for pattern classification

    Modern fuzzy min max neural networks for pattern classification by Al Sayaydeh, Osama Nayel Ahmad

    Published 2019
    “…To build an efficient classifier model, researchers have introduced hybrid models that combine both fuzzy logic and artificial neural networks. Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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  9. 9
    Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network

    Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network by Ismail Abdullah, Kalid Abdlkader Marsal

    Published 2024
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  10. 10
    Vector evaluated particle swarm optimization approach to solve assembly sequence planning problem

    Vector evaluated particle swarm optimization approach to solve assembly sequence planning problem by A. Mukred, Jameel A., A. Rahim, Ruzairi, Mohamad, Elmy Johana, Salh, Adeeb, Ashyap, Adel Y. I., Abdullah, Qazwan, AL-Fadhali, Najib, Al-Ameri, S., Al-Ashwal, Rania

    Published 2022
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  11. 11
    Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data

    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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  12. 12
    Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem

    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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  13. 13
    Adaptive RS-group scheduling for WiMAX multihop relay

    Adaptive RS-group scheduling for WiMAX multihop relay by Saeed, Rashid Abdelhaleem, Al-Talib , S.A., Al-Ahdal, T.A., Mohamad, H., Abbas, Majed, Ali, Bashir, Odeh, M.

    Published 2010
    “…This paper proposes mesh topology for IEEE 802.16j using adaptive RS group scheduling. The proposed scheduling algorithm introduces new signalling to support functions such as soft and hard horizontal-RS neighbour scanning, bandwidth request, forwarding of PDUs and connection management. …”
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  14. 14
    Designing and Developing an Intelligent Congkak

    Designing and Developing an Intelligent Congkak by Muhammad Safwan, Mohd Shahidan

    Published 2011
    “…Therefore the project want to try to rectify this issue by trying to develop an Intelligent Congkak System that also implemented NN and try answer research question such as this: “What is the best Congkak evaluation function for training NN for game playing?” and “Can Min-Max algorithm (MM) be speeded up by using NN as a forward-pruning method?”. …”
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  15. 15
    Performance comparison of differential evolution and particle swarm optimization in constrained optimization

    Performance comparison of differential evolution and particle swarm optimization in constrained optimization by Iwan, Mahmud, Akmeliawati, Rini, Faisal, Tarig, Al-Assadi, Hayder M.A.A.

    Published 2012
    “…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. This paper presents a comparative study for min-max constrained optimization using PSO and DE. …”
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  16. 16
    Design And Implementation Of Low Passband Ripple Digital Down Converter Filter For Software Defined Radio Transceiver

    Design And Implementation Of Low Passband Ripple Digital Down Converter Filter For Software Defined Radio Transceiver by Naghmash, Majid Salal

    Published 2011
    “…The proposed DDC filters incorporate of Remez algorithm and Mini-max algorithm to reduce the error rate in the filter response. …”
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  17. 17
    Improved handover decision algorithm using multiple criteria

    Improved handover decision algorithm using multiple criteria by Mohamed Abdullah, Radhwan, Abualkishik, Abedallah Zaid, Alwan, Ali Amer

    Published 2018
    “…Conventionally, a device that is mobile can be used to attain vertical handover functional by weighing in only an aspect, which refers to Received Signal Strength (RSS). …”
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  18. 18
    A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function

    A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function by Mahdi, F.P., Vasant, P., Abdullah-Al-Wadud, M., Watada, J., Kallimani, V.

    Published 2018
    “…Many-objective EED problems are defined by using a cubic criterion function, and a max/max price penalty factor is considered to convert all the objectives into a single objective to compare the final results with other well-known methods found in the literature like Lagrangian relaxation, particle swarm optimization, simulated annealing, and quantum-behaved bat algorithm. …”
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  19. 19
    A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function

    A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function by Mahdi, F.P., Vasant, P., Abdullah-Al-Wadud, M., Watada, J., Kallimani, V.

    Published 2018
    “…Many-objective EED problems are defined by using a cubic criterion function, and a max/max price penalty factor is considered to convert all the objectives into a single objective to compare the final results with other well-known methods found in the literature like Lagrangian relaxation, particle swarm optimization, simulated annealing, and quantum-behaved bat algorithm. …”
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  20. 20
    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems

    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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