Search Results - (( learning transformative learning algorithm ) OR ( program implementation developing algorithm ))

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    Speed control of separately excited dc motor using artificial intelligent approach by Bernard, Albinus

    Published 2013
    “…The effectiveness of the proposed method is verified by develop simulation model in MATLAB-Simulink program. …”
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    Thesis
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    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

    Published 2009
    “…Each web services are easily maintainable since there is loose coupling between interacting nodes. The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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    Industry 5.0 and Education 5.0: Transforming Vocational Education through Intelligent Technology by Zhang, Hongli, Leong, Wai Yie

    Published 2024
    “…By analyzing the research gaps in personalized learning paths, emotion-driven learning, crossdisciplinary integration, and long-term learning behavior analysis, the paper proposes four improved algorithms: the adaptive learning path generation algorithm, the emotion-driven personalized learning algorithm, the cross-disciplinary knowledge graph algorithm, and the long-term learning behavior prediction algorithm. …”
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    Article
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    Classification of fault and stray gassing in transformer by using duval pentagon and machine learning algorithms by Haw, Jia Yong, Mohd Yousof, Mohd Fairouz, Abd Rahman, Rahisham, Talib, Mohd Aizam, Azis, Norhafiz

    Published 2022
    “…However, there are times where the produce of stray gassing event might lead to fault indication in the transformer. Machine learning algorithms are used to classify the DGA data into normal condition and corresponding faults based on IEEE limits and Duval pentagon method. …”
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    Article
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    Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data by Terence Chia Yi Kai, Agus Saptoro, Zulfan Adi Putra, King Hann Lim, Wan Sieng Yeo, Jaka Sunarso

    Published 2025
    “…Industrial process time series data could be processed with ease by deep learning algorithms, particularly transformer-based models because of their multi-head attention mechanism. …”
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    Article
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    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation by Lateh, Masitah bdul

    Published 2020
    “…The proposed algorithm named as Box-Whisker Data Transformation considered all samples contain in a MLCC dataset in order to generate artificial samples. …”
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    Thesis
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    Development of an interactive learning tool for analysis of fast fourier transform from butterfly diagram by Mohamad Syeihri Bin Mohamad Ismail

    Published 2023
    “…By developing the software it will enhance the learning and application of signal analysis of Fast Fourier Transform. …”
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    CLASSIFICATION OF BEARING FAULTS USING EXTREME LEARNING MACHINE ALGORITHMS by TEH, CHOON KEONG

    Published 2017
    “…Therefore, this project introduces three learning algorithms which are Extreme Learning Machine (ELM), Finite Impulse Response Extreme Learning Machine (FIR-ELM) and Discrete Fourier Transform Extreme Learning Machine (DFT-ELM) to improve the bearing fault diagnosis accuracy and shorten the time used to train and test the neural network.…”
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    Final Year Project
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    Global-Local Partial Least Squares Discriminant Analysis And Its Extension In Reproducing Kernel Hilbert Space by Muhammad, Aminu

    Published 2021
    “…Thus, subspace learning techniques are employed to reduce the dimensionality of the data prior to employing other learning algorithms. …”
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    Thesis
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    Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid by Ab Hamid, Salbiah

    Published 2010
    “…The weight of each value in hidden layers will be considered during the learning process. LM algorithm is used to minimize the error during training and testing process. …”
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    Thesis
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    Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

    Published 2020
    “…For our research we did the comparisons between three Machine Learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Decision Tree, and one Deep Learning algorithm called Convolutional Neural Network (CNN), to find the optimal algorithm that best fits for the waste classification solution. …”
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    Article
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    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

    Published 2020
    “…The application of artificial intelligence techniques (e.g., machine learning and deep learning) in medical science is becoming increasingly important for intelligently transforming all available information into valuable knowledge. …”
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    Conference or Workshop Item
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