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  1. 1

    Enhancing hyperparameters of LSTM network models through genetic algorithm for virtual learning environment prediction by Ismanto, Edi, Ab Ghani, Hadhrami, Md Saleh, Nurul Izrin

    Published 2025
    “…Genetic algorithms for hyperparameter optimization significantly contributed, with the GA + LSTM + ADAGRAD model achieving 88% and 87% accuracy in the 7th and 9th models for BBB course data. …”
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    Article
  2. 2

    Resource scheduling algorithm with load balancing for cloud service provisioning by Priya, V., Sathiya Kumar, C., Kannan, R.

    Published 2019
    “…Increasing utilization of Virtual Machines through effective and fair load balancing is then achieved by dynamically selecting a request from a class using Multidimensional Queuing Load Optimization algorithm. …”
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    Article
  3. 3

    A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network by Almuslehi, Hussein Saad Mohammed

    Published 2023
    “…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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    Thesis
  4. 4

    An enhanced motion planning method for industrial robots based on the digital twin concept by Rui, Fan

    Published 2025
    “…By integrating an improved Artificial potential field method, A* algorithm, and a synergistic approach combining 3-5-3 polynomial interpolation with particle swarm optimization, we effectively address the challenges of dynamic obstacle avoidance and trajectory optimization. …”
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    Thesis
  5. 5

    A Data-driven Sigmoid-based Secretion Rate of Neuroendocrine-PID Control for TRMS System by Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Haszuraidah, Ishak

    Published 2021
    “…This paper investigated the implementation of datadriven sigmoid-based secretion rate of neuroendocrine-PID (SbSR-NEPID) within a twin-rotor MIMO system (TRMS), based on the adaptive safe experimentation dynamics (ASED) algorithm. …”
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    Conference or Workshop Item
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    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…The HFPSO technique hybridizes the Firefly Optimization (FFO) algorithm and the Particle Swarm Optimization (PSO) method to improve the exploitation and exploration strategies and enhance the convergence rate. …”
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    Thesis
  9. 9

    Performance comparison of non-invasive blood glucose level using artificial neural network and ultra-wide band antenna by Islam, Minarul Rafiqul, Sabira, Khatun, Kamarul Hawari, Ghazali, Mohd Mawardi, Saari, Shakib, Mohammed Nazmus, Mohamad Shaiful, Abdul Karim

    Published 2020
    “…Several experiments were carried out to investigate the optimal ANN learning algorithm (levenberg-marquardt (LM), resilient backpropagation (RP) and scaled conjugate gradient (SCG)) for performance comparison. …”
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    Conference or Workshop Item
  10. 10

    Machining optimization using Firefly Algorithm / Farhan Md Jasni by Md Jasni, Farhan

    Published 2020
    “…For this project, we will verify the Firefly Algorithm (FA) into finding total profit rate by optimizing the machining parameter of milling operation and compare the effectiveness of FA with other non¬conventional method. …”
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    Student Project
  11. 11

    Optimization of cnc turning parameters for minimizing temperature rise in aluminum using a genetic algorithm by Mimi Muzlina, Mukri

    Published 2024
    “…The genetic algorithm is used in this optimization because it is capable of searching for global optimal solutions since the configuration of the method can be very flexible, allowing it to be used for a variety of problems. …”
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    Thesis
  12. 12

    Optimization of mycelium growth using genetic algorithm for multi-objective functions by Muhamad Faiz, Abu Bakar

    Published 2019
    “…Through the implementation of selected multi-objective genetic algorithm, NSGA-ii was able to produce pareto front for optimizing both nitrogen concentration and the extension rate of the mycelium. …”
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    Undergraduates Project Papers
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    Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates by Yeong, Lin Koay, Hong, Seng Sim, Yong, Kheng Goh, Sing, Yee Chua, Wah, June Leong

    Published 2024
    “…The process of training neural networks heavily involves solving optimization problems. Most optimization algorithms use a !…”
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    Conference or Workshop Item
  15. 15

    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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    Undergraduates Project Papers
  16. 16

    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

    Published 2018
    “…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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    Conference or Workshop Item
  17. 17

    GENETIC ALGORITHM OPTIMIZED PACKET FILTERING by NURIKA, OKTA

    Published 2013
    “…n our research, we present a method to optimize packet filtering by genetic algorithm. …”
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    Thesis
  18. 18

    An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms by Ullah, Arif

    Published 2021
    “…The proposed HBAC algorithm was tested and compared with other stateof-the-art algorithms on 200 to 2000 even tasks by using CloudSim on standard workload format (SWF) data sets file size (200kb and 400kb). …”
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    Thesis
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    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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    Article