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  1. 1
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…First the effect of different combinations of GA operators on the performance of the model developed is studied. A proposed algorithm called modified GA, or MGA, is presented and a comparison between a simple GA and a modified GA is carried out. …”
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  2. 2
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…First the effect of different combinations of GA operators on the performance of the model developed is studied. A proposed algorithm called modified GA, or MGA, is presented and a comparison between a simple GA and a modified GA is carried out. …”
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  3. 3
    Model structure selection for a discrete-time non-linear system using genetic algorithm

    Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

    Published 2004
    “…First the effect of different combinations of GA operators on the performance of the model developed is studied. A proposed algorithm called modified GA, or MGA, is presented and a comparison between a simple GA and a modified GA is carried out. …”
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  4. 4
    Dynamic obstacle handling in multi-robot coverage

    Dynamic obstacle handling in multi-robot coverage by Tay, Wing Le

    Published 2024
    “…One of the key aspects in multi-robot coverage is dynamic obstacle handling, which involves robots avoiding dynamic obstacle during coverage task while reaching their respective goal positions. This report focuses on developing a multi-robot coverage algorithm with dynamic obstacle handling abilities, known as the Modified Lloyd’s algorithm with Velocity Obstacle (VO). …”
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    Final Year Project / Dissertation / Thesis
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  5. 5
    DEVELOPMENT OF DRIVER DROWSINESS DETECTION ALGORITHM

    DEVELOPMENT OF DRIVER DROWSINESS DETECTION ALGORITHM by YVONNE, PHUA YEE WUN

    Published 2022
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    Final Year Project Report / IMRAD
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  6. 6
    Facial features point localization using modified SIFT scale space / Zulfikri Paidi

    Facial features point localization using modified SIFT scale space / Zulfikri Paidi by Paidi, Zulfikri

    Published 2020
    “…Three tests were used on the original SIFT algorithm and modified SIFT. The first test is to evaluate the accuracy of the built-in vector feature. …”
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    Thesis
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  7. 7
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

    Published 2004
    “…First the effect of different combinations of GA operators on the performance of the model developed is studied. A proposed algorithm called modified GA, or MGA, is presented and a comparison between a simple GA and a modified GA is carried out. …”
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  8. 8
    Modified Image Enhancement Algorithm For Dorsal Hand Veins Imaging

    Modified Image Enhancement Algorithm For Dorsal Hand Veins Imaging by Gan, Siew Ling

    Published 2018
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    Monograph
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  9. 9
    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    Published 2014
    “…Second, the obtained results that included arrays of the top-ranked features were used as the initial population of a genetic algorithm to produce optimum arrays of features. Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. …”
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  10. 10
    Building an Algorithm for Measuring C Programming Assignments Quality

    Building an Algorithm for Measuring C Programming Assignments Quality by Muhd Zulhafriz Aadel bin Marzuki, Muhd Zulhafriz

    Published 2008
    “…The focuses of this final report is to provide a clear idea on the development of programming assignment’s quality measurement algorithm. …”
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    Final Year Project
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  11. 11
    Development of computer aided three-dimensional geometric modeler based on designer's idea in twodimensional

    Development of computer aided three-dimensional geometric modeler based on designer's idea in twodimensional by Haron, Habibollah

    Published 2006
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    Monograph
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  12. 12
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  13. 13
    A Method For Solving Mult-Objective Optimization Problem: Vector Evaluated Genetic Algorithm (Vega)

    A Method For Solving Mult-Objective Optimization Problem: Vector Evaluated Genetic Algorithm (Vega) by Tan, Tun Tai

    Published 2009
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    Final Year Project Report / IMRAD
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  14. 14
    Automated QT interval measurement using modified Pan-Tompkins algorithm with independent isoelectric line approach

    Automated QT interval measurement using modified Pan-Tompkins algorithm with independent isoelectric line approach by Jumahat, Shaliza, Gan, Kok Beng, Misran, Norbahiah, Islam, Mohammad Tariqul, Mahri, Nurhafizah, Ja'afar, Mohd. Hasni

    Published 2020
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  15. 15
    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)

    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589) by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod, Zaini, Bahtiar Jamili

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    Monograph
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  16. 16
    An Efficient Computational Algorithm for Solving Arbitrary Sylvester Matrix Equations in Fuzzy Control Theory (S/O 14179)

    An Efficient Computational Algorithm for Solving Arbitrary Sylvester Matrix Equations in Fuzzy Control Theory (S/O 14179) by Ahmad, Nazihah, Ibrahim, Haslinda

    Published 2021
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    Monograph
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  17. 17
    Design And Evaluation Of A Modified Csma/Cd Mac Protocol On Single-Channel Optical Local Area Network

    Design And Evaluation Of A Modified Csma/Cd Mac Protocol On Single-Channel Optical Local Area Network by Khairi, Kharina

    Published 2003
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  18. 18
    Development of optimization Alghorithm for uncertain non-linear dynamical system

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
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    Monograph
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  19. 19
    BASE: a bacteria foraging algorithm for cell formation with sequence data

    BASE: a bacteria foraging algorithm for cell formation with sequence data by Nouri, Hossein, Tang, Sai Hong, Baharudin, B. T. Hang Tuah, Mohd Ariffin, Mohd Khairol Anuar

    Published 2010
    “…The performance of the proposed algorithm is compared with that of a number of algorithms that are most commonly used and reported in the corresponding scientific literature, such as the CASE clustering algorithm for sequence data, the ACCORD bicriterion clustering algorithm and modified ART1, and using a defined performance measure known as group technology efficiency and bond efficiency. …”
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  20. 20
    Smart Agriculture Economics and Engineering: Unveiling the Innovation Behind AI-Enhanced Rice Farming

    Smart Agriculture Economics and Engineering: Unveiling the Innovation Behind AI-Enhanced Rice Farming by Zun Liang, Chuan, Tham, Ren Sheng, Tan, Chek Cheng, Abraham Lim, Bing Sern, David Lau, King Luen, Chong, Yeh Sai

    Published 2024
    “…The analysis utilized a novel modified stacked Multiple Linear Regression- -Support Vector Regression (MLR- -SVR) algorithm, and a novel modified stacked MLR- -Support Vector Regression (MLR- -SVR) algorithm, demonstrating high predictive capability, especially in a limited dataset environment, which the algorithms’ superiority ranked utilizing modified Taguchi-based VIseKriterijumska Optimizacija I Kompromisno Resenje (Taguchi-based VIKOR) multi-criteria decision-making algorithm. …”
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