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  1. 1
    A performance analysis of association rule mining algorithms

    A performance analysis of association rule mining algorithms by Fageeri, S.O., Ahmad, R., Alhussian, H.

    Published 2016
    “…In this paper, we evaluate the performance of association rule mining algorithms in-terms of execution times and memory usage using the CPU profiler of Java VisualVM. …”
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  2. 2
    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh

    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

    Published 2020
    “…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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  3. 3
    PREDICTING THE PRICE OF COTTON USING RNN AND LSTM

    PREDICTING THE PRICE OF COTTON USING RNN AND LSTM by MOHAMAD, AHMAD LUKMAN

    Published 2020
    “…The accuracy of each machine learning algorithm will be recorded and analyze to come up with the best model for the dataset. …”
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  4. 4
    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks

    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

    Published 2014
    “…EFMM and EFMM2, are proposed to address a number of limitations in the original FMM learning algorithm. In EFMM, three heuristic rules are introduced to improve the hyperbox expansion, overlap test, and contraction processes. …”
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  5. 5
    Understanding the nature of oil fluctuations using 1 neutral network moving average: A study on the returns of crude oil futures

    Understanding the nature of oil fluctuations using 1 neutral network moving average: A study on the returns of crude oil futures by Phooi M’ng, J.C., Zainudin, R., Aziz, A.A.

    Published 2015
    “…The results here suggest that it is worthwhile to design, build and develop more robust, machine learning algorithms like neural networks enhanced moving average technical indicator to enhance portfolio returns. …”
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  6. 6
    Polynomial neural network for solving Caputo-conformable fractional Volterra–Fredholm integro-differential equation with three-point non-local boundary conditions

    Polynomial neural network for solving Caputo-conformable fractional Volterra–Fredholm integro-differential equation with three-point non-local boundary conditions by Alsa’di, Kawthar, Nik Long, Nik Mohd Asri, Senu, Norazak, Eshkuvatov, Z.K.

    Published 2025
    “…A hybrid technique, combining a polynomial neural network (PNN) with an extreme learning machine algorithm without using any activation functions, is developed. …”
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  7. 7
    Non-fungible token based smart manufacturing to scale Industry 4.0 by using augmented reality, deep learning and industrial Internet of Things

    Non-fungible token based smart manufacturing to scale Industry 4.0 by using augmented reality, deep learning and industrial Internet of Things by Ahmed Khan, Fazeel, Ibrahim, Adamu Abubakar

    Published 2023
    “…The next phase was deploying deep learning algorithms on a dataset having data generated from IIoT devices and sensors. …”
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  8. 8
    Efficient ML technique in blockchain-based solution in carbon credit for mitigating greenwashing

    Efficient ML technique in blockchain-based solution in carbon credit for mitigating greenwashing by Raja Segaran, Bama, Mohd Rum, Siti Nurulain, Hafez Ninggal, Mohd Izuan, Mohd Aris, Teh Noranis

    Published 2025
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  9. 9
    Modeling of Functional Electrical Stimulation (FES): Powered Knee Orthosis (PKO) assisted gait exercise in post-stroke rehabilitation / Adi Izhar Che Ani

    Modeling of Functional Electrical Stimulation (FES): Powered Knee Orthosis (PKO) assisted gait exercise in post-stroke rehabilitation / Adi Izhar Che Ani by Che Ani, Adi Izhar

    Published 2023
    “…In the human gait model, three Machine Learning algorithms were used: Gaussian Process Regression, Support Vector Machine, and Decision Tree. …”
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