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  1. 1

    Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Ramarao, Taj, Mohammed Baloch

    Published 2008
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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    Conference or Workshop Item
  2. 2

    Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Rama Rao

    Published 2009
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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  3. 3

    Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines by K.S.R., Rao, Z.F., Desta

    Published 2008
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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  4. 4

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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    Thesis
  5. 5
  6. 6

    Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks by K.S.R, Rao, F. D., Zahlay

    Published 2008
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi's Method. …”
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    Conference or Workshop Item
  7. 7

    Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin by Burhanudin, Kharismi

    Published 2018
    “…The process continues repeatedly to track maximum power depending on the swarmsize of the MPPT algorithm. In order to validate this technique simulation was conducted using MATLAB SIMULINK software in order to observe and identify the output power extracted from the PV panel. …”
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    Thesis
  8. 8

    Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System by Jye Yun, Fam, Shen Yuong, Wong, Hazrul, Mohamed Basri, Mohammad Omar, Abdullah, Kasumawati, Lias, Saad, Mekhilef

    Published 2021
    “…All simulations were performed using MATLAB software to show the power characteristics extracted from the PEMFC system. …”
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    Article
  9. 9

    Vehicle detection for vision-based intelligent transportation systems using convolutional neural network algorithm by Khalifa, Othman Omran, Wajdi, Muhammad H., Saeed, Rashid A., Hassan Abdalla Hashim, Aisha, Ahmed, Muhammed Z., Ali, Elmustafa Sayed

    Published 2022
    “…Specifically, the paper utilized the YOLOv5s architecture coupled with k-means algorithm to perform anchor box optimization under different illumination levels. …”
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    Article
  10. 10

    Hybrid particle swarm optimization for robust digital image watermarking by Tao, Hai, Jasni, Mohamad Zain, Abdalla, Ahmed N., Mohammad Masroor, Ahmed

    Published 2011
    “…This paper presents an image watermarking algorithm for the optimization between robustness and transparency which is recently considered as one of the most challenging issues. …”
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    Article
  11. 11

    Grey wolf optimization and differential evolution-based maximum power point tracking controller for photovoltaic systems under partial shading conditions by Kishore, D. J. Krishna, Mohamed, M. R., Sudhakar, K., Peddakapu, K.

    Published 2022
    “…The simulation results disclose that the hybrid GWO-DE approach shows a greater performance as compared to other studied methods with respect to convergence time, accuracy, extracted power, and efficiency. …”
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    Article
  12. 12

    High impedance fault detection and localization in 11kV distribution system / Mohd Syukri Ali by Mohd Syukri , Ali

    Published 2018
    “…Subsequent algorithm simulation results show that the proposed methods are able to detect and subsequently locate the faults with high accuracies. …”
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    Thesis
  13. 13

    A new metaheuristic-based MPPT controller for photovoltaic systems under partial shading conditions and complex partial shading conditions by Kishore, Dokala Janandra Krishna, Mohd Rusllim, Mohamed, Sudhakar, K., Peddakapu, K.

    Published 2024
    “…The proposed method is developed in MATLAB/Simulink software. The system is examined under distinct irradiation conditions and compared their performance with other methods. …”
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    Article
  14. 14

    Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System by Jye Yun, Fam

    Published 2025
    “…All simulations were conducted using MATLAB software to demonstrate the PEMFC power characteristics and output power extraction. …”
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    Thesis
  15. 15

    Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

    Published 2015
    “…In this study, a software defect prediction framework that combines metaheuristic optimization methods for feature selection and parameter optimization, with meta learning methods for solving imbalanced class problem on datasets, which aims to improve the accuracy of classification models has been proposed. …”
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    Thesis
  16. 16

    Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

    Published 2002
    “…We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. …”
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    Undergraduates Project Papers
  17. 17

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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    Article
  18. 18

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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    Article
  19. 19

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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    Article
  20. 20

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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    Article