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  1. 1
    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system

    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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  2. 2
    Automated Model Generation Approach Using MATLAB

    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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  3. 3
    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system

    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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  4. 4
    Using simulated annealing algorithm for optimization of quay cranes and automated guided vehicles scheduling

    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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  5. 5
    Different mutation and crossover set of genetic programming in an automated machine learning

    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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  6. 6
    Different mutation and crossover set of genetic programming in an automated machine learning

    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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  7. 7
    Forward-Backward Time Stepping with Automated Edge-preserving Regularization Technique for Wood Defects Detection

    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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  8. 8
    Federated deep learning for automated detection of diabetic retinopathy

    Federated deep learning for automated detection of diabetic retinopathy by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani

    Published 2022
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  9. 9
    Reactive approach for automating exploration and exploitation in ant colony optimization

    Reactive approach for automating exploration and exploitation in ant colony optimization by Allwawi, Rafid Sagban Abbood

    Published 2016
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  10. 10
    Fuzzy state space modeling for solving inverse problems in multivariable dynamic systems

    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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  11. 11
    Development and tuning of bacteria foraging optimization algorithm on cell formation in cellular manufacturing system

    Development and tuning of bacteria foraging optimization algorithm on cell formation in cellular manufacturing system by Nouri, Hossein, Tang, Sai Hong, Mohd Ariffin, Mohd Khairol Anuar, Baharudin, B. T. Hang Tuah, Samin, Razali

    Published 2013
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  12. 12
    Modelling of Twin Rotor MIMO system

    Modelling of Twin Rotor MIMO system by Dang Huu, T., Ismail, I.B.

    Published 2017
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  13. 13
    A comparative analysis of metaheuristic algorithms in fuzzy modelling for phishing attack detection

    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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  14. 14
    Yaw rate and sideslip control using h-infinity-pid controller during automated lane change manoeuver

    Yaw rate and sideslip control using h-infinity-pid controller during automated lane change manoeuver by Zainal, Zainab

    Published 2021
    “…This research aims to propose a simple PID tuning algorithm and to investigate the possibility of utilising H¥ synthesis during the automated LC manoeuvre by initiating the estimated steering wheel angle of the driver’s model at a constant speed of 80 km=h. …”
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  15. 15
    Deep Learning Based image segmentation for expensive soil desiccation crack recognition and qualification

    Deep Learning Based image segmentation for expensive soil desiccation crack recognition and qualification by Ling, Hui Yean

    Published 2025
    “…Compared to traditional approaches, deep learning models, particularly with DeepLabv3+ variants, produced more reliable crack segmentation masks, thus enabling more accurate quantification of crack geometrical parameters, as demonstrated by lower error rates. …”
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  16. 16
    Neural network modeling for prediction of weld bead geometry in laser microwelding

    Neural network modeling for prediction of weld bead geometry in laser microwelding by Ismail, Mohd Idris Shah, Okamoto, Yasuhiro, Okada, Akira

    Published 2013
    “…The backpropagation with the Levenberg-Marquardt training algorithm was used to train the neural network model. …”
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  17. 17
    System identification for an autonomous quadrotor using extended and unscented kalman filters

    System identification for an autonomous quadrotor using extended and unscented kalman filters by Abas, Norafizah, Legowo, Ari, Akmeliawati, Rini

    Published 2011
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  18. 18
    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment

    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

    Published 2017
    “…On the other hand, consideration of all parameters in an APP model makes the generation of a master production schedule deeply complicated especially in real-world APP problems, where input data or parameters are frequently imprecise (fuzzy) due to incomplete or un obtain able information and daily changes patterns of demand and manufacturers capacity (Sakalhet al., 2010). …”
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  19. 19
    Simulation Models for Straight Lines Images Detection Using Hough Transform

    Simulation Models for Straight Lines Images Detection Using Hough Transform by Qussay, Abbas Salih Al-Badri

    Published 2001
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  20. 20
    Expression invariant face recognition using multi-stage 3D face fitting with 3D morphable face model

    Expression invariant face recognition using multi-stage 3D face fitting with 3D morphable face model by Alomari, Abdallah A., Khalid, Fatimah, O. K. Rahmat, Rahmita Wirza, Abdullah, Muhamad Taufik

    Published 2010
    “…The idea of the model is to update parameters at each stage in the fitting process. …”
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