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    Real-Time Flood Inundation Map Generation Using Decision Tree Machine Learning Method: Case Study of Kelantan River Basins by Sidek L.M., Basri H., Marufuzzaman M., Deros A.M., Osman S., Hassan F.A.

    Published 2024
    “…Additionally, to predict the flood depth, a trained Decision Tree (DT)-based sorting algorithm is used in this method. …”
    Book chapter
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    Reinforcement Learning Algorithm for Optimising Durian Irrigation Systems: Maximising Growth and Water Efficiency by Ramli, Muhammad Shahrul Azwan, Zainal Abidin, Mohamad Shukri, Hasan, Nor Shahida, Md Reba, Mohd Nadzri, Kolawole, Keshinro Kazeem, Ardiansyah, Rizqi Andry, Mpuhus, Sikudhan Lucas

    Published 2024
    “…This study presents a Reinforcement Learning-based algorithm designed to optimise irrigation for Durio Zibethinus (i.e., durian) trees, aiming to maximise tree growth and reduce water usage. …”
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    Article
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    Investigating photovoltaic solar power output forecasting using machine learning algorithms by Essam Y., Ahmed A.N., Ramli R., Chau K.-W., Idris Ibrahim M.S., Sherif M., Sefelnasr A., El-Shafie A.

    Published 2023
    “…To address this issue, continuous research and development is required to determine the best machine learning (ML) algorithm for PV solar power output forecasting. …”
    Article
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    Sales prediction for Adha Station by using predictive analytics by Mohd Mokhid, Muhammad Amier Latieff

    Published 2025
    “…Additionally, pre-processing is conducted using the RapidMiner application prior to mapping the cleaned data with three distinct algorithms for predictive analysis: Decision Tree, Random Forest, and Multiple Linear Regression techniques. …”
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    Student Project
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    Detection of multiple mangoes using histogram of oriented gradient technique in aerial monitoring by Mohd Ali, Nursabillilah, Karis, Mohd Safirin, Mohd Sobran, Nur Maisarah, Bahar, Mohd Bazli, Oh, Kok Ken, Mat Ibrahim, Masrullizam, Johan, Nurul Fatiha

    Published 2016
    “…It differentiates the mango and its leaf based on the images captured on real scene and thus forecast the growth rate of the mango tree for time being. …”
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    Article
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    Application of Machine Learning for Daily Forecasting Dam Water Levels by Almubaidin, Ahmed, Winston C.A.A., El-Shajie A.

    Published 2024
    “…In this study, seven machine learning algorithms were developed to predict a dam water level daily based on the historical data of the dam water level. …”
    Article
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    Forecasting of meteorological drought using ensemble and machine learning models by Pande C.B., Sidek L.M., Varade A.M., Elkhrachy I., Radwan N., Tolche A.D., Elbeltagi A.

    Published 2025
    “…Therefore, the Matern GPR model was identified as the finest ML algorithm for predicting SPI-3 and SPI-6 associated with other algorithms. …”
    Article
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    Appliance level stand-by burst forecast modelling using machine learning techniques by Mustafa, Abid

    Published 2020
    “…This work proposes a technique to model power consumption data and presents a comparative study of five different machine learning algorithms to study their suitability to forecast an appliance's state and standby burst. …”
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    Thesis
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    Implementation of machine learning algorithms for streamflow prediction of Dokan dam by Sarmad Dashti Latif, Mr.

    Published 2023
    “…Daily inflow and rainfall time-series data have been collected as two hydrological parameters to forecast reservoir inflow using the developed deep learning long-short term memory (LSTM) model and conventional machine learning models, namely support vector machine (SVM), random forest (RF), and boosted regression tree (BRT). …”
    text::Thesis
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    Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR) models by Elbeltagi A., Pande C.B., Kumar M., Tolche A.D., Singh S.K., Kumar A., Vishwakarma D.K.

    Published 2024
    “…Due to limited historical data for drought monitoring and forecasting available in the central India of Maharashtra state, implementing machine learning (ML) algorithms could allow for the prediction of future drought events. …”
    Article