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  1. 1
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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  2. 2
    SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing

    SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing by Abd, Wamidh Jwdat

    Published 2019
    “…This work uses iterative smoothing algorithm to find an alternative path with less distance and energy consumption. …”
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  3. 3
    Energy efficient path reconstruction in wireless sensor network using iPath

    Energy efficient path reconstruction in wireless sensor network using iPath by Hasan, Sazlinah, Abd, Wamidh Jwdat, Ariffin, Ahmad Alauddin

    Published 2019
    “…This work uses iterative boosting algorithm to find an alternative path with less distance and energy consumption. …”
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  4. 4
    Visdom: Smart guide robot for visually impaired people

    Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

    Published 2025
    “…Core functionalities such as path planning, autonomous movement, voice feedback, and app-to-robot communication have been thoroughly tested and optimized. …”
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    Final Year Project / Dissertation / Thesis
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  5. 5
    Development of web based learning content of animation algorithm on searching and sorting techniques / Nur Linda Abdi Nur

    Development of web based learning content of animation algorithm on searching and sorting techniques / Nur Linda Abdi Nur by Abdi Nur, Nur Linda

    Published 2007
    “…The objectives of this project is to develop self-learning environment in learning searching and sorting algorithm, enhance understanding of student in learning searching and sorting technique and to apply web-based learning in computer science subject, which focus on courses that use searching and sorting algorithm.…”
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  6. 6
    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments

    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
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  7. 7
    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif

    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

    Published 2014
    “…Support Vector Machine (SVM) is among the popular learning algorithm for classification in soft computing techniques. …”
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    Research Reports
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  8. 8
    A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market

    A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market by Mohd. Ridzuan Ab. Khalil, Azuraliza Abu Bakar

    Published 2023
    “…This study aims to develop a univariate and multivariate stock market forecasting model using three deep learning algorithms and compare the performance of those models. …”
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  9. 9
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…By using the proposed algorithm, the sparse coefficients are learned by exploiting the relationships among different multi-view features and leveraging the knowledge from multiple related tasks. …”
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  10. 10
    Predictive Modelling of Stroke Occurrence among Patients using Machine Learning

    Predictive Modelling of Stroke Occurrence among Patients using Machine Learning by Sures, Narayasamy, Thilagamalar, Maniam

    Published 2023
    “…This study proposes a machine learning-based approach to predict the likelihood of stroke among patients. …”
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  11. 11
    A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting

    A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting by Md Salleh N.S., Suliman A., Jorgensen B.N.

    Published 2023
    Conference Paper
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  12. 12
    Performance comparison of CNN and LSTM algorithms for arrhythmia classification

    Performance comparison of CNN and LSTM algorithms for arrhythmia classification by Hassan, S.U., Zahid, M.S.M., Husain, K.

    Published 2020
    “…Analyzing the performance of these algorithms will further assist in the development of an enhanced deep learning model that offers improved performance. …”
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    Conference or Workshop Item
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  13. 13
    Development of deep reinforcement learning based resource allocation techniques in cloud radio access network

    Development of deep reinforcement learning based resource allocation techniques in cloud radio access network by Amjad, Iqbal

    Published 2022
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    Final Year Project / Dissertation / Thesis
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  14. 14
    Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks

    Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks by Krishnasamy, Ganesh, Paramesran, Raveendran

    Published 2019
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  15. 15
    Machine learning in predicting anti-money laundering compliance with protection motivation theory among professional accountants

    Machine learning in predicting anti-money laundering compliance with protection motivation theory among professional accountants by Masrom, S., Tarmizi, M.A., Halid, S., Rahman, R.A., Abd Rahman, A.S., Ibrahim, R.

    Published 2023
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  16. 16
    A systematic literature review of deep learning neural network for time series air quality forecasting

    A systematic literature review of deep learning neural network for time series air quality forecasting by Zaini N., Ean L.W., Ahmed A.N., Malek M.A.

    Published 2023
    Review
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  17. 17
    RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION

    RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION by CATUR ANDRYANI, NUR AFNY

    Published 2010
    “…Science and technology development has the tendency of learning from nature where human also try to develop artificial intelligent by imitating biological neuron network which is popularly termed Artificial Neural Network (ANN). …”
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  18. 18
    Loan Eligibility Classification Using Machine Learning Approach

    Loan Eligibility Classification Using Machine Learning Approach by Law, Paul Lik Pao

    Published 2023
    “…This research paper presents a study on loan eligibility classification using a machine learning approach by comparing the performance of three Machine Learning algorithms which were Logistic Regression, Random Forest, and Decision Tree. …”
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    Undergraduates Project Papers
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  19. 19
    Music Recommender System Using Machine Learning Content-Based Filtering Technique

    Music Recommender System Using Machine Learning Content-Based Filtering Technique by Foong, Kin Hong

    Published 2022
    “…These are the popular algorithm for unsupervised learning, a machine learning method to analyse and cluster datasets. …”
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    Undergraduates Project Papers
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  20. 20
    Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches

    Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches by Al Mahmud, Suaib, Kamarulariffin, Abdurrahman, Mohd Ibrahim, Azhar, Haja Mohideen, Ahmad Jazlan

    Published 2024
    “…In this review paper, a comprehensive review of mobile robot navigation algorithms has been conducted. The findings suggest that, even though the self-learning algorithms require huge amounts of training data and have the possibility of learning erroneous behavior, they possess huge potential to overcome challenges rarely addressed by the other traditional algorithms. …”
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