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  1. 1
    Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi

    Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi by Rahimi, Ahmad Faris

    Published 2017
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  2. 2
    Artificial neural network (ANN) modeling & validation to predict compression index of tropical soft soil

    Artificial neural network (ANN) modeling & validation to predict compression index of tropical soft soil by Yong, Shirley Xiao Wei

    Published 2010
    “…Therefore, many settlement prediction methods have focused on correlations with in-situ tests, such as the Cone Penetration Test (CPT), Standard Penetration Test (SPT), Dilatometer Modulus Test (DMT), plate load test, and pressure-meter test. …”
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    Final Year Project Report / IMRAD
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  3. 3
    Optimization of Multilayer Perceptron (MLP) network training algorithms for agrwood oil quality separation / Noratikah Zawani Mahabob ... [et al.]

    Optimization of Multilayer Perceptron (MLP) network training algorithms for agrwood oil quality separation / Noratikah Zawani Mahabob ... [et al.] by Mahabob, Noratikah Zawani, Mohd Yusoff, Zakiah, Ismail, Nurlaila, Taib, Mohd Nasir

    Published 2020
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  4. 4
    Solving Sudoku puzzles in Binary Integer Linear Programming using Branch and Bound algorithm / Ahida Waliyyah Ahmad Fuad

    Solving Sudoku puzzles in Binary Integer Linear Programming using Branch and Bound algorithm / Ahida Waliyyah Ahmad Fuad by Ahmad Fuad, Ahida Waliyyah

    Published 2024
    “…This study explores the application of a Binary Integer Linear Programming (BILP) model combined with the Branch and Bound (B&B) algorithm to solve Sudoku puzzles. …”
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  5. 5
    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
    “…The adequacy of the developed models is tested using one-step-ahead prediction and correlation-based model validation tests. …”
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  6. 6
    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
    “…The adequacy of the developed models is tested using one-step-ahead prediction and correlation-based model validation tests. …”
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  7. 7
    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
    “…The adequacy of the developed models is tested using one-step-ahead prediction and correlation-based model validation tests. …”
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  8. 8
    Priority and dynamic quantum time algorithms for central processing unit scheduling

    Priority and dynamic quantum time algorithms for central processing unit scheduling by Mohammed, Maysoon A.

    Published 2018
    “…For statistical analysis, a Wilcoxon non-parametric test is used to test and validate the results of the experiments. …”
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  9. 9
    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm

    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

    Published 2024
    “…The framework was subsequently verified and validated through expert reviews and experimental testing. …”
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  10. 10
    Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.]

    Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.] by Pusadan, Mohammad Yazdi, Rabbani, Mohammad Abied, Ardiansyah, Rizka, Ngemba, Hajra Rasmita

    Published 2023
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  11. 11
    A Hybrid Multi-objective Integrated JAYA-Evolutionary Programming (MOIJEP) Algorithm for Under Voltage Load Shedding (UVLS) Scheme in Bulk Power System

    A Hybrid Multi-objective Integrated JAYA-Evolutionary Programming (MOIJEP) Algorithm for Under Voltage Load Shedding (UVLS) Scheme in Bulk Power System by Shukor S.F.A., Musirin I., Hamid Z.A., Senthil Kumar A.V., Mansor M.H., Salimin R.H.

    Published 2025
    “…MOIJEP integrates the features in the original Jaya algorithm into the conventional Evolutionary Programming (EP). …”
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  12. 12
    Euclidean space data projection classifier with cartesian genetic programming (CGP)

    Euclidean space data projection classifier with cartesian genetic programming (CGP) by WK Wong, Gopal Lenin, Tan, Terence, Ali Chekima

    Published 2018
    “…This research work is a preliminary work which proposes an evolutionary-based classifier using a simplified Cartesian Genetic Programming (CGP) evolutionary algorithm. Instead on using evolutionary generated rule sets, the CGP generates i) a reference coordinate ii) projection functions to project data into a new 3 Dimensional Euclidean space. …”
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  13. 13
    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
    “…The adequacy of the developed models is tested using one-step-ahead prediction and correlation-based model validation tests. …”
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  14. 14
    AI recommendation penetration testing tool for cross-site scripting: support vector machine algorithm

    AI recommendation penetration testing tool for cross-site scripting: support vector machine algorithm by Salim, Nur Saadah, Saad, Shahadan

    Published 2025
    “…This research introduces a new approach to enhancing cybersecurity by integrating Support Vector Machine (SVM) algorithms with penetration testing to develop a recommendation system focused on Cross-Site Scripting (XSS) attack detection. …”
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  15. 15
    Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan

    Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan by Mohd Hanis, Rani, Abdullah, Embong

    Published 2013
    “…Using 10-fold cross validation for each algorithm, it was found that decision tree was the best algorithm with 83.6944% correctness. …”
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  16. 16
    Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat

    Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat by Fatima, Jannat

    Published 2022
    “…Hyper-parameter tuning has been used in all the algorithms using k-fold cross validation to have the best accuracy and to avoid the over-fitting issue. …”
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  17. 17
    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms

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

    Published 2017
    “…A new formulation for the multi-objective optimal power flow (MOOPF) problem that considers DG is introduced. The proposed algorithms have been examined and validated using the IEEE 30-bus and IEEE 118-bus test systems. …”
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  18. 18
    Indoor Navigation Algorithm For Mobile Robot

    Indoor Navigation Algorithm For Mobile Robot by Y.M. Alkasim, Osman Mudthir Elfadil, Abass, Esra Bashir

    Published 2016
    “…Set of experiments presented to validate our system using MATLAB program. Testing verified that good accuracy, sufficient for navigation, was achieved. …”
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  19. 19
    Enhancing obfuscation technique for protecting source code against software reverse engineering

    Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

    Published 2019
    “…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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  20. 20
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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