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  1. 1
    Machine learning‐based approach for bandwidth and frequency prediction of circular SIW antenna

    Machine learning‐based approach for bandwidth and frequency prediction of circular SIW antenna by Alam, Md Mahabub, Nurhafizah, Abu Talip Yusof, Ahmad Afif, Mohd Faudzi, Tomal, Md Raihanul Islam, Haque, Md Ershadul, Rahman, Md. Suaibur

    Published 2025
    “…A predictive ML framework was developed using six regression algorithms trained on significant geometrical parameters, such as ring slot radius, via diameter, and feedline width. …”
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  2. 2
    Integration of grey analysis with artificial neural network for classification of slope failure

    Integration of grey analysis with artificial neural network for classification of slope failure by Deris A.M., Solemon B., Omar R.C.

    Published 2023
    “…This study employs an "artificial neural network" (ANN) to predict the slope failures based on historical circular slope cases. Using the feed-forward back-propagation algorithm with a multilayer perceptron network, ANN is a powerful ML method capable of predicting the complex model of slope cases. …”
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  3. 3
    Image Classification for Age-related Macular Degeneration Screening Using Hierarchical Image Decompositions and Graph Mining

    Image Classification for Age-related Macular Degeneration Screening Using Hierarchical Image Decompositions and Graph Mining by Mohd Hanafi Ahmad Hijazi, Chuntao Jiang, Frans Coenen, Yalin Zheng

    Published 2011
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  4. 4
    A comparative study of supervised machine learning approaches for slope failure production

    A comparative study of supervised machine learning approaches for slope failure production by Deris A.M., Solemon B., Omar R.C.

    Published 2023
    “…This study employs an "artificial neural network" (ANN) to predict the slope failures based on historical circular slope cases. Using the feed-forward back-propagation algorithm with a multilayer perceptron network, ANN is a powerful ML method capable of predicting the complex model of slope cases. …”
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  5. 5
    Effect of particle size on second law of thermodynamics analysis of Al2O3 nanofluid: Application of XGBoost and gradient boosting regression for prognostic analysis

    Effect of particle size on second law of thermodynamics analysis of Al2O3 nanofluid: Application of XGBoost and gradient boosting regression for prognostic analysis by Kumar K P., Alruqi M., Hanafi H.A., Sharma P., Wanatasanappan V.V.

    Published 2025
    “…Prognostic models were developed using two sophisticated machine learning algorithms, XGBoost and Gradient Boosting Regression (GBR). …”
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