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    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system by Ayop Azmi, Nurnajmin Qasrina Ann, Pebrianti, Dwi, Abas, Mohammad Fadhil, Bayuaji, Luhur

    Published 2023
    “…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper�parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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    Article
  2. 2

    Automated Model Generation Approach Using MATLAB by Xia, Likun

    Published 2011
    “…An estimation algorithm is then required in order to obtain parameters for these models. …”
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    Book Section
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    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohammad Fadhil, Abas, Bayuaji, Luhur

    Published 2023
    “…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper-parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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    Article
  5. 5

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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    Conference or Workshop Item
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    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
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    Using simulated annealing algorithm for optimization of quay cranes and automated guided vehicles scheduling by Homayouni, Seyed Mahdi, Tang, Sai Hong, Ismail, Napsiah, Mohd Ariffin, Mohd Khairol Anuar

    Published 2011
    “…In this paper, an integrated scheduling of quay cranes and automated guided vehicles is formulated as a mixed integer linear programming model. …”
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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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    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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    Forward-Backward Time Stepping with Automated Edge-preserving Regularization Technique for Wood Defects Detection by Yong, Guang

    Published 2019
    “…Therefore, two automated procedures are developed to determine these parameters iteratively. …”
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    Thesis
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    Fuzzy state space modeling for solving inverse problems in multivariable dynamic systems by Ismail, Razidah

    Published 2005
    “…This model is used for optimization of input parameters in multivariable dynamic systems. …”
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    Thesis
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    A comparative analysis of metaheuristic algorithms in fuzzy modelling for phishing attack detection by Noor Syahirah, Nordin, Mohd Arfian, Ismail, Tole, Sutikno, Shahreen, Kasim, Rohayanti, Hassan, Zalmiyah, Zakaria, Mohd Saberi, Mohamad

    Published 2021
    “…The optimization method derives from the metaheuristic algorithm. Therefore, the aim of this study is to make a comparative analysis between the metaheuristic algorithms in fuzzy modelling. …”
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    Article