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    Optimization machining parameters in pocket milling using genetic algorithm and mastercam by Abdullah, Haslina, Isa, Nurshafinaz, Zakaria, Mohamad Shukri

    Published 2023
    “…It shows that optimization based on GA is capable of reducing production time in the machining process.…”
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    Conference or Workshop Item
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    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…The algorithms are evaluated using 30 benchmark functions of the CEC2014 benchmark suite, and then applied to solve PCB drill path optimization case study. …”
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    Thesis
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    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
    “…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short-term daily electricity load in Peninsular Malaysia. …”
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    Article
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    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
    “…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short‑term daily electricity load in Peninsular Malaysia. …”
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    Article
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    Differential search algorithm in multi machine power system stabilizers for damping oscillations by Islam N.N., Hannan M.A., Mohamed Z., Shareef H.

    Published 2023
    “…Simulations are conducted in linear and non-linear models of power system to verify the robustness of proposed algorithm. A comprehensive investigation is conducted to compare the performance of DSA based PSSs with the tuned PSSs using bacterial foraging optimization algorithm (BFOA) and particle swarm optimization (PSO) in terms of convergence, improvements of electromechanical modes and system damping over oscillations. …”
    Article
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    To study the multi-objective optimization of EDM using genetic algorithm by Fairuz, Idris

    Published 2013
    “…In the process of the study, the second- order mathematical model has been create as a fitness function using MATLAB software to generate multi-objective optimization responses using Genetic Algorithms, peak current, pulse-on time, pulse-off time and servo voltage are act as input of parameter setting. …”
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    Undergraduates Project Papers
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    Single Machine Connected Infinite Bus system tuning coordination control using biogeography-based optimization algorithm by Kasilingam G., Pasupuleti J., Bharatiraja C., Adedayo Y.

    Published 2023
    “…In this paper, the design of hybrid coordinated damping controller (power system stabilizer (PSS) and proportional integral derivative (PID) controller) is articulated as an optimization problem. The objective function J is framed using Integral square error (ISE) and the optimal parameters can be obtained by minimizing the objective function using the proposed Biogeography Based Optimization (BBO) algorithm. …”
    Article
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    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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    Article
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    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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    Article
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    Damping power system oscillation using elitist differential search algorithm in multi machine power system by Niamul Islam N., Hannan M.A., Mohamed A., Hussain S.

    Published 2023
    “…In this paper, damping power system oscillations is presented using the Elitist differential search algorithm (Elitist-DSA) in a multi-machine system. …”
    Article
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    Optimization of multi-holes drilling path using particle swarm optimization by Najwa Wahida, Zainal Abidin

    Published 2022
    “…This research aims to model and optimise multi-hole drilling problems using Particle Swarm Optimisation (PSO) algorithm. …”
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    Thesis
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    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO) by Mohd Erwan Mazalan

    Published 2022
    “…Optimization algorithms can be used to solve Non-deterministic Polynomial (NP) hard problem like system management. …”
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    Academic Exercise
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    Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms : A review by Kauthar, Mohd Daud, Ananda, Ridho, Suhaila, Zainudin, Chan, Weng Howe, Moorthy, Kohbalan, Nurul Izrin, Md Saleh

    Published 2023
    “…This review paper summarizes research on the hybrid of constraint-based models and machine learning algorithms in optimizing valuable metabolites. …”
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    Article
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    Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training by Lee, Sen Tan, Zainuddin, Zarita, Ong, Pauline

    Published 2020
    “…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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    Article