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  1. 1

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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    Thesis
  2. 2

    One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network by Rahim, Muhammad Fitri

    Published 2012
    “…By using 'seen' and 'unseen' of electrical energy demand data were used to test the performance of the proposed algorithm. Based on result obtained, it shows that IWO learning algorithm is capable to produce accurate prediction load demand. …”
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    Student Project
  3. 3

    Pairwise Test Suite Generation Using Adaptive Teaching Learning-Based Optimization Algorithm with Remedial Operator by Fakhrud, Din, Kamal Z., Zamli

    Published 2019
    “…ATLBO is a recent enhanced variant of Teaching Learning-based Optimization (TLBO) algorithm that adaptively applies its search operations using a Mamdani-type fuzzy inference system. …”
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    Conference or Workshop Item
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    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. …”
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    Article
  6. 6

    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat Algorithm (BA) was hybrid based Multi-Layer Feedforward Neural Network (MLFNN) for modeling the temperature operating of photovoltaic module. …”
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    Article
  7. 7

    Q-learning whale optimization algorithm for test suite generation with constraints support by Hassan, Ali Abdullah, Salwani, Abdullah, Kamal Z., Zamli, Rozilawati, Razali

    Published 2023
    “…This paper introduces a new variant of a metaheuristic algorithm based on the whale optimization algorithm (WOA), the Q-learning algorithm and the Exponential Monte Carlo Acceptance Probability called (QWOA-EMC). …”
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    Article
  8. 8

    Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat Algorithm (BA) was hybrid based Multi-Layer Feedforward Neural Network (MLFNN) for modeling the temperature operating of photovoltaic module. …”
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    Thesis
  9. 9

    An oppositional learning prediction operator for simulated kalman filter by Zuwairie, Ibrahim, Kamil Zakwan, Mohd Azmi, Badaruddin, Muhammad, Mohd Falfazli, Mat Jusof, Nor Azlina, Alias, Nor Hidayati, Abdul Aziz, Mohd Ibrahim, Shapiai

    Published 2018
    “…The proposed prediction operator is based on oppositional learning. The results show that using CEC2014 as benchmark problems, the SKF algorithm with oppositional learning prediction operator outperforms the original SKF algorithm in most cases.…”
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    Conference or Workshop Item
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    Opposition-based learning simulated kalman filter for Numerical optimization problems by Mohd Falfazli, Mat Jusof

    Published 2016
    “…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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    Research Book Profile
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    Performance evaluation for different intrusion detection system algorithms using machine learning by Zarir, Mustafa Nadhim

    Published 2018
    “…The objectives of this project is to evaluate the performance of various intrusion detection algorithms based on machine learning. The algorithms considered are the Naive Bays Algorithm, Decision Tree Algorithm and Hybrid Algorithm for different datasets. …”
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    Thesis
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    Distributed learning based energy-efficient operations in small cell networks by Mughees, Amna

    Published 2023
    “…Simulation results demonstrate improved performance in power consumption, load, sum rate, utility, learning rate, convergence, and energy efficiency for small base stations (SBSs) and user equipment (UEs) compared to four benchmarked algorithms, including WMMSE, game theory, Q-learning, and DRL. …”
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    Thesis
  18. 18

    A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem by Kamal Z., Zamli, Fakhrud, Din, Ahmed, Bestoun S., Bures, Miroslav

    Published 2018
    “…Instead, we rely on the Q-learning algorithm (based on the penalty and reward mechanism) to dynamically identify the best operation during runtime. …”
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    Article
  19. 19

    Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition by Yew W.H., Fat Chau C., Mahmood Zuhdi A.W., Syakirah Wan Abdullah W., Yew W.K., Amin N.

    Published 2024
    “…Recently, more robust algorithms based on deep reinforcement learning (DRL) have been proposed. …”
    Conference Paper
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    Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique by Lai V., Huang Y.F., Koo C.H., Ahmed A.N., Sherif M., El-Shafie A.

    Published 2024
    “…In this study, an attempt via metaheuristic algorithms, namely the Harris Hawks Optimisation (HHO) Algorithm and the Opposite Based Learning of HHO (OBL-HHO) are made to minimise the water deficit as well as mitigate floods at downstream of the Klang Gate Dam (KGD). …”
    Article