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  1. 1
    Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia

    Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia by Zaini, Farah Anishah, Sulaima, Mohamad Fani, Wan Abdul Razak, Intan Azmira, Othman, Mohammad Lutfi, Mokhlis, Hazlie

    Published 2024
    “…Finally, the load forecasting model based on LSSVM-IBFOA is constructed using mean absolute percentage error (MAPE) as the objective function. …”
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  2. 2
    Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia

    Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia by Sulaima, Mohamad Fani, Zaini, Farah Anishah, Wan Abdul Razak, Intan Azmira, Othman, Mohammad Lutfi, Mokhlis, Hazlie

    Published 2024
    “…Finally, the load forecasting model based on LSSVM‑IBFOA is constructed using mean absolute percentage error (MAPE) as the objective function. …”
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  3. 3
    Optimized speed controller for induction motor drive using quantum lightning search algorithm

    Optimized speed controller for induction motor drive using quantum lightning search algorithm by Ali J.A., Hannan M.A., Mohamed A.

    Published 2023
    Conference Paper
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  4. 4
    Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals

    Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals by Homayouni, Seyed Mahdi

    Published 2012
    “…Therefore, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm, were developed to optimize the integrated scheduling of handling equipment. …”
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  5. 5
    Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH

    Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH by Norhafidzah, Mohd Saad

    Published 2021
    “…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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  6. 6
    Renewable sources-based automatic load frequency control of interconnected systems using chaotic atom search optimization

    Renewable sources-based automatic load frequency control of interconnected systems using chaotic atom search optimization by Irudayaraj, Andrew Xavier Raj, Abdul Wahab, Noor Izzri, Premkumar, Manoharan, Mohd Radzi, Mohd Amran, Sulaiman, Nasri, Veerasamy, Veerapandiyan, Farade, Rizwan A., Islam, Mohammad Zohrul

    Published 2022
    “…Initially, the proposed IASO is validated using a classical benchmark function and its performance is compared with ASO algorithm. …”
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  7. 7
    ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation

    ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation by Hannan M.A., Abdolrasol M.G., Mohamed R., Al-Shetwi A., Ker P., Begum R., Muttaqi K.

    Published 2023
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  8. 8
    Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid

    Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid by Abdul Hamid, Zulkiffli

    Published 2013
    “…Eventually, in providing an effective load shedding scheme with reliable amount of load power to be shed, an intuitive Fuzzy Inference System (FIS) was designed using FVSI as the criterion when designing its membership functions and rules. …”
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  9. 9
    Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid

    Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid by Abdul Hamid, Zulkiffli

    Published 2013
    “…Eventually, in providing an effective load shedding scheme with reliable amount of load power to be shed, an intuitive Fuzzy Inference System (FIS) was designed using FVSI as the criterion when designing its membership functions and rules. …”
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  10. 10
    Particle Swarm Optimization Algorithm Based Fuzzy Controller for Solid-State Transfer Switch Toward Fast Power Transfer and Power Quality Mitigation

    Particle Swarm Optimization Algorithm Based Fuzzy Controller for Solid-State Transfer Switch Toward Fast Power Transfer and Power Quality Mitigation by Hannan M.A., Sebastian G., Al-Shetwi A.Q., Ker P.J., Rahman S.A., Mansor M., Muttaqi K.M., Uddin M.

    Published 2024
    “…A PSO-based FLC (PSOF) fitness function is introduced to optimize the load transfer performance by minimizing the mean squared error (MSE) in a short period of time. …”
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  11. 11
    Normalized SPSA for Hammerstein model identification of twin rotor and electro-mechanical positioning systems

    Normalized SPSA for Hammerstein model identification of twin rotor and electro-mechanical positioning systems by Nik Mohd Zaitul Akmal, Mustapha, Mohd Ashraf, Ahmad

    Published 2025
    “…For the TRS, the N-SPSA improved the mean objective function by 18.09 % compared to the average multi-verse optimizer sine-cosine algorithm (AMVO-SCA) and 3.42 % compared to the norm-limited (NL-SPSA), while reducing the computational load by 60 % compared to the AMVO-SCA. …”
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  12. 12
    Determining penetration limit of central distributed generation topology in radial distribution networks

    Determining penetration limit of central distributed generation topology in radial distribution networks by Suliman, Mohamed Saad Abdelgadir

    Published 2021
    “…The beta probability density functions were used to model the photovoltaic generation, while the normal probability density functions were used to model the load demand. …”
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  13. 13
    Energy balancing mechanisms for decentralized routing protocols in wireless sensor networks

    Energy balancing mechanisms for decentralized routing protocols in wireless sensor networks by Saleh, Ahmed Mohammed Shamsan

    Published 2012
    “…It is based on Ant Colony Optimization (ACO) meta heuristic, which is adopted to enhance the paths with the best-quality function. …”
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  14. 14
    A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties

    A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties by Norhafidzah, Mohd Saad, Muhamad Zahim, Sujod, Mohd Ikhwan, Muhammad Ridzuan, Mohammad Fadhil, Abas, Mohd Shawal, Jadin, Mohd Fadzil, Abdul Kadir

    Published 2024
    “…The Active Power Loss (APL) index was calculated considering the risk of uncertain photovoltaic generation and urban load distributions. The Monte Carlo Probability Density Function method was initially used to manage uncertainties. …”
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  15. 15
    Modeling and Optimization of Tapered Rectangular Thin-walled Columns Subjected to Oblique Loading for Impact Energy Absorption

    Modeling and Optimization of Tapered Rectangular Thin-walled Columns Subjected to Oblique Loading for Impact Energy Absorption by Siti Aishah, Rusdan, Tarlochan, Faris, Mohamad Rusydi, Mohamad Yasin

    Published 2013
    “…The optimal design is obtained by using the constrained nonlinear multivariable optimization algorithm provided by MATLAB. …”
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  16. 16
    Pid-aco vibration controller with magnetorheological damper for wind turbine tower / Mahmudur Rahman

    Pid-aco vibration controller with magnetorheological damper for wind turbine tower / Mahmudur Rahman by Mahmudur , Rahman

    Published 2019
    “…Next, PID control parameters are optimized with ACO method based on the vibration displacement as objective function to achieve the optimal damping force which is used to encounter vibrations under different excitation frequencies and loading conditions. …”
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  17. 17
    Optimal under voltage load shedding based on stability index by using artificial neural network

    Optimal under voltage load shedding based on stability index by using artificial neural network by Sharman, Sundarajoo

    Published 2020
    “…This optimal load shedding algorithm does not over shed or under shed the load. …”
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  18. 18
    Optimization of load frequency control permancein two-area power system with PID controller using ICA and GSA algorithms / Mumuney Nurullahi Lekan

    Optimization of load frequency control permancein two-area power system with PID controller using ICA and GSA algorithms / Mumuney Nurullahi Lekan by Mumuney Nurullahi , Lekan

    Published 2018
    “…The change in the system is signified by the change in the system frequency and tie-line (T-L) load. …”
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  19. 19
    Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations

    Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations by Nouri, Hossein, Tang, Sai Hong

    Published 2013
    “…This paper investigates the first applications of this emerging novel optimization algorithm to the cell formation (CF) problem. …”
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  20. 20
    A contactless computer vision system for underwater walking and jogging gait analysis using YOLO-pose and Multi-CNN BiLSTM architecture

    A contactless computer vision system for underwater walking and jogging gait analysis using YOLO-pose and Multi-CNN BiLSTM architecture by Cheng, Tong Bao, Khairuddin, Uswah

    Published 2025
    “…A comparison of hyperparameter optimization algorithms was conducted, with the combination of multivariate tree-structured Parzen estimators (MultiTPE) and Hyperband identified as the optimal approach. …”
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