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  1. 1
    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Notably, the SPSA and GSPSA based methods only produced the optimal design parameter at the final iteration while it may keep a better design parameter during the tuning process if it has a memory feature. …”
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  2. 2
    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Notably, the SPSA and GSPSA based methods only produced the optimal design parameter at the final iteration while it may keep a better design parameter during the tuning process if it has a memory feature. …”
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  3. 3
    Nomadic people optimizer (NPO) for large-scale optimization problems

    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…The proposed algorithm simulates the behavior of the nomads when they are searching for life sources (water or grazing fields). …”
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  4. 4
    Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm

    Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali, Mohd Helmi, Suid, Mohd Zaidi, Mohd Tumari

    Published 2024
    “…These results underscore the efficacy of the SEDA method in providing optimal PID control parameters while reducing computational burdens by 52% compared to other multi-agent optimization-based methods.…”
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  5. 5
    Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling

    Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling by Shimailawi, Shatha Abdulhadi Muthana

    Published 2022
    “…The proposed models and algorithm can be used to solve the multi-objective GMS problem while the new parameters’ values can be used to obtain optimal or near optimal maintenance scheduling of generators. …”
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  6. 6
    Fuzzy clustering method and evaluation based on multi criteria decision making technique

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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  7. 7
    Hybrid optimization approach to estimate random demand

    Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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  8. 8
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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  9. 9
    Improved smoothed functional algorithmsoptimized pid controller for efficient speed regulation of wind turbines

    Improved smoothed functional algorithmsoptimized pid controller for efficient speed regulation of wind turbines by Mohd Ashraf, Ahmad, Yoganathan, G., Muhammad Ikram, Mohd Rashid, Hao, Mok Ren, Mohd Zaidi, Mohd Tumari

    Published 2025
    “…This study introduces a novel approach for PID controller tuning in wind turbine systems using single-agent optimization methods, specifically the memory smoothed functional algorithm (MSFA) and norm-limited smoothed functional algorithm (NL-SFA). …”
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  10. 10
    Computational dynamic support model for social support assignments around stressed individuals among graduate students

    Computational dynamic support model for social support assignments around stressed individuals among graduate students by Al-Shorman, Roqia Rateb

    Published 2020
    “…However, the existing configuration algorithms are often randomized and static. Thus, their results can vary significantly between multiple runs. …”
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  11. 11
    Information Theoretic-based Feature Selection for Machine Learning

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…The second test evaluates IFS in a controlled study using simulated datasets. …”
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  12. 12
    A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis

    A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Saleh, Basma Jumaa, Omar, Zaid, As’ari, Muhammad Amir, Bhateja, Vikrant, Izhar, Lila Iznita

    Published 2025
    “…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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  13. 13
    Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA

    Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA by Javed, E., Faye, I., Malik, A.S., Abdullah, J.M.

    Published 2017
    “…From the simulated data, the similarity index between the extracted BCG and the simulated BCG showed the effectiveness of the proposed method in BCG removal. …”
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  14. 14
    Artificial neural network and inverse solution method for assisted history matching of a reservoir model

    Artificial neural network and inverse solution method for assisted history matching of a reservoir model by Negash, B.M., Vel, A., Elraies, K.A.

    Published 2017
    “…This allows to directly simulate the trained neural network and avoid the use of objective function and optimization algorithm. …”
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  15. 15
    Model-free controller design based on simultaneous perturbation stochastic approximation

    Model-free controller design based on simultaneous perturbation stochastic approximation by Mohd Ashraf, Ahmad

    Published 2015
    “…In order to evaluate the effectiveness of our proposed scheme, a wind farm model with dynamic characterization of wake interaction between turbines is used and then the proposed method is applied to the Horns Rev wind farm. …”
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  16. 16
    Automated calibration of baseline model for energy conservation using multi-objective Evolutionary Programming (EP) / Ahmad Amiruddin Mohammad Aris

    Automated calibration of baseline model for energy conservation using multi-objective Evolutionary Programming (EP) / Ahmad Amiruddin Mohammad Aris by Mohammad Aris, Ahmad Amiruddin

    Published 2019
    “…The co-simulation approach is proposed to obtain optimal solution of the thermal comfort-baseline energy configuration due to complexity in finding the trade-off between variables in reducing discrepancies between simulated energy consumption and measured data, furthermore leveraging automated computational calibration process. …”
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  17. 17
    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks

    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

    Published 2025
    thesis::doctoral thesis
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  18. 18
    Time-variant online auto-tuned pi controller using pso algorithm for high accuracy dual active bridge dc-dc converter

    Time-variant online auto-tuned pi controller using pso algorithm for high accuracy dual active bridge dc-dc converter by Suliana, Ab Ghani, Hamdan, Daniyal, Norazila, Jaalam, Nur Huda, Ramlan, Norhafidzah, Mohd Saad

    Published 2022
    “…This paper proposes a time-variant online auto-tuned PI controller using a particle swarm optimization (PSO) algorithm for the 200 kW DAB system. …”
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  19. 19
    Time-Variant online Auto-Tuned PI controller using PSO algorithm for high accuracy dual active bridge DC-DC converter

    Time-Variant online Auto-Tuned PI controller using PSO algorithm for high accuracy dual active bridge DC-DC converter by Suliana, Ab Ghani, Hamdan, Daniyal, Norazila, Jaalam, Nur Huda, Ramlan, Norhafidzah, Mohd Saad

    Published 2022
    “…This paper proposes a time-variant online auto-tuned PI controller using a particle swarm optimization (PSO) algorithm for the 200 kW DAB system. …”
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  20. 20
    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…To obtain the unknown vector of parameters of the MHTan, three heuristic optimization algorithms are employed to minimize the sum of squared residuals. …”
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