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  1. 1
    Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri

    Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri by Mohd Asri, Azinuddin

    Published 2022
    “…The Random Forest algorithm was the best algorithm compared to the artificial neural network, which produced the highest R2 (0.998) and lowered RSME (55.067). …”
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  2. 2
    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN)

    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
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    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN)

    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
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  4. 4
    Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease

    Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

    Published 2021
    “…The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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  5. 5
    Automated diagnosis of diabetes using entropies and diabetic index

    Automated diagnosis of diabetes using entropies and diabetic index by Acharya, U.R., Fujita, H., Bhat, S., Koh, J.E.W., Adam, M., Ghista, D.N., Sudarshan, V.K., Chua, K.P., Chua, K.C., Molinari, F., Ng, E.Y.K., Tan, R.S.

    Published 2016
    “…These redundant features are eliminated by using six feature selection algorithms: Student's t-test, Receiver Operating Characteristic Curve (ROC), Wilcoxon signed-rank test, Bhattacharyya distance, Information entropy and Fuzzy Max-Relevance and Min-Redundancy (MRMR). …”
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