Search Results - (( basic optimization method algorithm ) OR ( using machine learning algorithm ))

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  1. 1

    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

    Published 2019
    “…As network attackers keep changing their methods of attack execution to evade the deployed intrusion-detection systems (IDS), machine learning (ML) algorithms have been introduced to boost the performance of the IDS. …”
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    Conference or Workshop Item
  2. 2

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
    “…The strategies applied showed that the final accuracy obtained through the training after implementing a modification in the algorithm is at 81% accuracy rate compared to the basic model that recorded its final accuracy at 79% accuracy rate. …”
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    Thesis
  3. 3

    Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

    Published 2019
    “…Those problems lend themselves to the realm of optimization. Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
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    Thesis
  4. 4

    Review and bibliometric analysis of AI-driven advancements in healthcare by Wang, Yi Jie, Choo, Wei Chong, Ng, Keng Yap

    Published 2024
    “…Research shows that "algorithm", "machine learning", "deep learning", "controlled study", "major clinical study" and "healthcare delivery" as well as "decision support systems" are key topics for research. …”
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    Article
  5. 5

    Predictive modeling and feature attribution of CO₂ adsorption on LDH-derived materials using machine learning approach by Pinto, Mavin Jason, Sharath, S. S., Sudhakar, K., Priya, S. Shanmuga, Thirunavukkarasu, I.

    Published 2025
    “…Moderate calcination of the material emerges as the optimal synthesis window, which results in balanced porosity, structural stability, and basic site density. …”
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    Article
  6. 6

    Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

    Published 2022
    “…The objective of this project is to develop the Windows malware detection model using supervised machine learning in Decision Tree, K-NN and Naïve Bayes, to evaluate the performance of malware detection in term of testing and training of the features selection and to compare the accuracy detection model in all three machine learning algorithms. …”
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    Student Project
  7. 7

    Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

    Published 2002
    “…We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. …”
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    Undergraduates Project Papers
  8. 8

    E4ML: Educational Tool for Machine Learning by Sainin, Mohd Shamrie, Siraj, Fadzilah

    Published 2003
    “…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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    Conference or Workshop Item
  9. 9

    Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

    Published 2024
    “…Furthermore, the taxonomy was used to evaluate the most recent machine learning algorithm and analysis. …”
    Article
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    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

    Published 2024
    “…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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    Thesis
  12. 12

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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    Thesis
  13. 13

    Propose a New Machine Learning Algorithm based on Cancer Diagnosis by Ali, Mohammed Hasan, Kohbalan, Moorthy, Anad, Mohammed Morad, Mohammed, Mohammed Abdulameer

    Published 2018
    “…There are many machine learning algorithms proposed for multi-category classification problems in the cancer diagnosis area. …”
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    Article
  14. 14

    CLASSIFICATION OF BEARING FAULTS USING EXTREME LEARNING MACHINE ALGORITHMS by TEH, CHOON KEONG

    Published 2017
    “…Therefore, this project introduces three learning algorithms which are Extreme Learning Machine (ELM), Finite Impulse Response Extreme Learning Machine (FIR-ELM) and Discrete Fourier Transform Extreme Learning Machine (DFT-ELM) to improve the bearing fault diagnosis accuracy and shorten the time used to train and test the neural network.…”
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    Final Year Project
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    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. …”
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    Article
  17. 17

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. …”
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    Article
  18. 18

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…Meanwhile, the proposed QOJaya algorithm produces better results than the basic Jaya method in terms of solution optimality and convergence speed. …”
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    Thesis
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    Octane number prediction for gasoline blends using convolution neural network / Zhu Yue by Zhu , Yue

    Published 2021
    “…Machine performance learning models depend to a large extant to the data quality used train the model. …”
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    Thesis