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  1. 1
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…All the algorithm for the engine has been developed by using Java script language. …”
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  2. 2
    Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive

    Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive by Hannan M.A., Ali J.A., Mohamed A., Amirulddin U.A.U., Tan N.M.L., Uddin M.N.

    Published 2023
    Conference Paper
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  3. 3
    Q-REINFORCEMENT LEARNING BASED MULTI-AGENT BELLMANFORD ROUTING ALGORITHM FOR SMART MICROGRID COMMUNICATION NETWORK

    Q-REINFORCEMENT LEARNING BASED MULTI-AGENT BELLMANFORD ROUTING ALGORITHM FOR SMART MICROGRID COMMUNICATION NETWORK by SINGH, NIHARIKA

    Published 2021
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  4. 4
    Study of machine learning in computer vision using Raspberry Pi

    Study of machine learning in computer vision using Raspberry Pi by Chong, Kah Luo

    Published 2024
    text::Final Year Project
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  5. 5
    Multi-agent reinforcement learning for Bai ethnic traditional dwelling protection in Dali : cultural identity-oriented community relationship optimization and urbanization adaptation algorithm.

    Multi-agent reinforcement learning for Bai ethnic traditional dwelling protection in Dali : cultural identity-oriented community relationship optimization and urbanization adaptati... by Xiaohua, Qian, Neilson Ilan, Mersat, Haslina, Hashim, Bemen Wong, Win Keong

    Published 2025
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  6. 6
    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar

    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

    Published 2006
    “…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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  7. 7
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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  8. 8
    Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach

    Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach by Shabbir Ahmed, Omar, Syed Mohamed Ali, Jaffar, Aabid, Abdul, Hrairi, Meftah, Mohd Yatim, Norfazrina Hayati

    Published 2024
    “…Subsequently, simulation data from numerous cases are utilized to identify the best parameter combination using machine learning algorithms. …”
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  9. 9
    PREDICTIVE MODELING OF DIMENSIONAL ACCURACIES IN 3D PRINTING USING ARTIFICIAL NEURAL NETWORK

    PREDICTIVE MODELING OF DIMENSIONAL ACCURACIES IN 3D PRINTING USING ARTIFICIAL NEURAL NETWORK by Sivaraos, Kumaran K., Dharsyanth R., Amran M., Shukor S.M., Pujari S., Ramasamy D., Vatesh U.K., Mahdi Al-Obaidi A.S.H., Ramesh S., Lee K.Y.S.

    Published 2024
    “…The ANN model was developed using MATLAB software, employing training functions and learning algorithms to optimize the neural network architecture. …”
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  10. 10
    Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller

    Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller by Sepeeh, Muhamad Syazmie

    Published 2022
    “…The function of the ANN was to improve speed-tracking performance, and the learning rate of the ANN inside the indirect FOC’s structure trained using the Levenberg-Marquardt (LM) algorithm was varied in order to increase speed-tracking accuracy when combined with the improved ANN speed controller. …”
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  11. 11
    Predictive modeling of dimensional accuracies in 3D printing using artificial neural network

    Predictive modeling of dimensional accuracies in 3D printing using artificial neural network by Subramonian, Sivarao, Kumaran, K., Dharsyanth, R., Md Ali, Mohd Amran, Salleh, Mohd Shukor, Pujari, Satish, Ramasamy, Devarajan, Vatesh, Umesh Kumar, Mahdi Al-Obaidi, Abdulkareem Sh, Ramesh, S., Lee, Kit Yee Sara

    Published 2023
    “…The ANN model was developed using MATLAB software, employing training functions and learning algorithms to optimize the neural network architecture. …”
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  12. 12
    Context enrichment framework for sentiment analysis in handling word ambiguity resolution

    Context enrichment framework for sentiment analysis in handling word ambiguity resolution by Yusof, Nor Nadiah

    Published 2024
    “…For classification performances, optimization of machine learning parameters and exploration of deep learning approaches can be applied for further enhancement.…”
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  13. 13
    Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models.

    Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models. by Kwad, Ayad Mahmood

    Published 2022
    “…This research introduces a developed method for online system identification based on the Hammerstein and Wiener nonlinear block-oriented structure with the artificial neural networks (NN) advantages and recursive weighted least squares algorithm for optimizing neural network learning in real-time. …”
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  14. 14
    Development of a Neural-Fuzzy Model for Machinability Data Selection in Turning Process

    Development of a Neural-Fuzzy Model for Machinability Data Selection in Turning Process by Kong, Hong Shim

    Published 2008
    “…The developed neural-fuzzy model should be further considered in a wider range of real-world machining processes for learning and prescribing knowledge.…”
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