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  1. 1

    An intelligent DDoS attack detection tree-based model using Gini index feature selection method by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik, Atigh, Hayate El

    Published 2023
    “…This paper proposes a novel intelligent DDoS attack detection model based on a Decision Tee (DT) algorithm and an enhanced Gini index feature selection method. …”
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    Article
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    Application of sampling-based motion planning algorithms in autonomous vehicle navigation by Khaksar, Weria, Mohamed Sahari, Khairul Salleh, Tang, Sai Hong

    Published 2016
    “…In this chapter, a novel sampling-based navigation architecture is introduced, which employs the optimal properties of RRT* planner and the low running time property of low-dispersion sampling-based algorithms. …”
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  4. 4

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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  5. 5

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A.

    Published 2022
    “…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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  6. 6

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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    Article
  7. 7

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

    Published 2022
    “…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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    Article
  8. 8

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

    Published 2023
    “…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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    Article
  9. 9

    Decision tree-based approach for online management of PEM fuel cells for residential application by Mohd Rusllim, Mohamed

    Published 2004
    “…A database is extracted from a previously-performed Genetic Algorithm (GA)-based optimization has been used to create a suitable decision tree, which was intended for generalizing the optimization results. …”
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    Thesis
  10. 10

    Reverse migration prediction model based on machine learning / Azreen Anuar by Anuar, Azreen

    Published 2024
    “…And the third objective is to evaluate reverse migration prediction model based on machine learning analysis. For this purpose, three (3) algorithms have been assessed, namely, the Random Forest, Decision Tree, and Gradient Boosted Tree. …”
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  11. 11

    Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob by Mahabob, Noratikah Zawani

    Published 2022
    “…This research proposes an intelligent technique for grading agarwood essential oil based on its chemical properties using the artificial neural network (ANN) technique. …”
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    Thesis
  12. 12

    Knowledge-based system developement for the game congkak / Syah Ali Reza Yaacob by Yaacob, Syah Ali Reza

    Published 2006
    “…Therefore, the Minimax algorithm is not applicable. The players are human and a goal-based agent. …”
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    Thesis
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    Decision tree-based approach for online management of pem fuel cells for residential application by Mohamed, Mohd Rusllim

    Published 2004
    “…A database was extracted from a previously�performed Genetic Algorithm (GA)-based optimization that has been used to create a suitable decision tree, which was intended for generalizing the optimization results. …”
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    Thesis
  15. 15

    Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

    Published 2021
    “…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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    Enhancing fairness and efficiency in teacher placement based on staff placement model: an intelligent teacher placement selection model for Ministry of Education Malaysia by Shamsul Saniron, Zulaiha Ali Othman, Abdul Razak Hamdan

    Published 2025
    “…The effectiveness of ITPS was evaluated using five machine learning algorithms: J48, Decision Tree, Naïve Bayes, Random Forest, and K-Nearest Neighbors. …”
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    Article
  19. 19

    Insomnia audio therapy mobile application with music recommender system / Nur Azmina Mohamad Zamani, Nasiroh Omar and Nur Damira Huda Azmi by Mohamad Zamani, Nur Azmina, Omar, Nasiroh, Azmi, Nur Damira Huda

    Published 2022
    “…For the machine learning training and testing purposes, data was collected based on the simulated run of the proposed insomnia audio therapy mobile application. …”
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  20. 20

    White root disease auto-detection system for rubber trees based on dynamic electro-biochemical latex properties / Mohd Suhaimi Sulaiman by Sulaiman, Mohd Suhaimi

    Published 2019
    “…The selected most optimized models were then used to classify between healthy trees and white root infected trees based on single input, double input and triple input categories. …”
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    Thesis