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  1. 1
    The forecasting of poverty using the ensemble learning classification methods

    The forecasting of poverty using the ensemble learning classification methods by Zamzuri, Muhammad Haziq Adli, Nadilah, Sofian, Hassan, Raini

    Published 2023
    “…This research was conducted to forecast poverty using classification methods. Random Forest and Extreme Gradient Boosting (XGBoost) algorithms were applied to forecast poverty since they are supervised learning algorithms that use the ensemble learning approach for classification. …”
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  2. 2
    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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  3. 3
    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System

    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

    Published 2020
    “…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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  4. 4
    Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living

    Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living by Hamza, Manar Ahmed, Hassan Abdalla Hashim, Aisha, Motwakel, Abdelwahed, Elhameed, Elmouez Samir Abd, Osman, Mohammed, Kumar, Arun, Singla, Chinu, Munjal, Muskaan

    Published 2024
    “…In this view, this research develops an arithmetic optimization algorithm with deep learning based tweets classification (AOADL-TC) approach for sustainable living. …”
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  5. 5
    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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  6. 6
    Combining deep and handcrafted image features for MRI brain scan classification

    Combining deep and handcrafted image features for MRI brain scan classification by Hasan, Ali M., Jalab, Hamid A., Meziane, Farid, Kahtan, Hasan, Al-Ahmad, Ahmad Salah

    Published 2019
    “…In this paper, a deep learning feature extraction algorithm is proposed to extract the relevant features from MRI brain scans. …”
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  7. 7
    Real-time implementation of H∞ controller for UAV helicopter using MATLAB-based embedded programming approach

    Real-time implementation of H∞ controller for UAV helicopter using MATLAB-based embedded programming approach by Tijani, Ismaila, Akmeliawati, Rini, Legowo, Ari

    Published 2015
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  8. 8
    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System

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

    Published 2019
    “…The incorporation of a single parallel hidden layer feed-forward neural network to the Fast Learning Network (FLN) architecture gave rise to the improved Extreme Learning Machine (ELM). …”
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  9. 9
    Implementation of Real-time Simple Edge Detection on FPGA

    Implementation of Real-time Simple Edge Detection on FPGA by Mohd Shukor, Mohd Nasir, Lo, H. H., Sebastian , Patrick

    Published 2005
    “…The resulting edge detection images showed that a simple edge detection algorithm was implemented on Cyclone II FPGA for real-time image processing.…”
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  10. 10
    Needleman wunsch implementation for SPAM/UCE inline filter

    Needleman wunsch implementation for SPAM/UCE inline filter by Tamil E.M., Idris M.Y.I., Thong C.M., Jali M.Z., Madihah Mohd Saudi

    Published 2024
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  11. 11
    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja

    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

    Published 2004
    “…This thesis also provides an explanation about the advantages. functions, characteristics. the degree of complexity in A • algorithm and its implementation in real-world application. …”
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  12. 12
    Implementation of Color Filtering on FPGA

    Implementation of Color Filtering on FPGA by Mohd Shukor, Mohd Nasir, Lo, H. H., Sebastian, Patrick

    Published 2007
    “…The functionality of the algorithm is first verified in Matlab, simulating the expected output of the system before implementing it onto the FPGA development board. …”
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  13. 13
    An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets

    An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets by Abdul Muqtasid, Rushdi

    Published 2025
    “…The k-Nearest Neighbour (k-NN) algorithm is one of the most widely used Instance-Based Learning methods due to its simplicity and ease of implementation. …”
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  14. 14
    Implementation of real-time simple edge detection on FPGA

    Implementation of real-time simple edge detection on FPGA by P., Sebastian, M.N.B.M., Shukor, H.H., Lo

    Published 2007
    “…The resulting edge detection images showed that a simple edge detection algorithm was implemented on Cyclone II FPGA for real-time image processing. …”
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  15. 15
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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  16. 16
    DC motor control using LQR algorithm

    DC motor control using LQR algorithm by Adezeno, Sagoli Olid

    Published 2008
    “…An application in Matlab called Simulink is used as tools for algorithm implementation. Simulink is chosen due to its block diagram implementation and its creation of user interface which allowing interfacing with programs in others languages. …”
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    Undergraduates Project Papers
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  17. 17
    Implementation of repetitive control algorithm in reducing vibration using MATLAB/SIMULINK / Mohamad Zuhairy Mohamed

    Implementation of repetitive control algorithm in reducing vibration using MATLAB/SIMULINK / Mohamad Zuhairy Mohamed by Mohamed, Mohamad Zuhairy

    Published 2008
    “…However the repetitive controller can be implementing to the real system such as “smart spring”. …”
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    Student Project
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  18. 18
    Implementation of color filtering on FPGA

    Implementation of color filtering on FPGA by P., Sebastian, M.N.B.M., Shukor, H.H., Lo

    Published 2007
    “…The functionality of the algorithm is first verified in Matlab, simulating the expected output of the system before implementing it onto the FPGA development board. …”
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  19. 19
    The effects of compiler optimizations in face recognition system

    The effects of compiler optimizations in face recognition system by Shuhaizar, Daud, Khalib, Z.I.K, R. Badlishah, Ahmad, Mohamad Rizon, Mohamed Juhari

    Published 2009
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  20. 20
    Quantum Processing Framework And Hybrid Algorithms For Routing Problems

    Quantum Processing Framework And Hybrid Algorithms For Routing Problems by Soltan Aghaei, Mohammad Reza

    Published 2010
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