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  1. 1
    A performance analysis of association rule mining algorithms

    A performance analysis of association rule mining algorithms by Fageeri, S.O., Ahmad, R., Alhussian, H.

    Published 2016
    “…The results of the CPU profiler of Java VisualVM showed that Binary-Based algorithm performs better than Eclat algorithm in-terms of both execution times and memory usage. …”
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  2. 2
    Performance evaluation of real-time multiprocessor scheduling algorithms

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…We hyave used the CPU profiler of Oracle JavaTM VisualVM to monitor the execution of LRE-TL as well as USG algorithms. …”
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  3. 3
    Customised fitness function of evolutionary algorithm for optimization of car park space / Ahmad Syahir Ab. Aziz

    Customised fitness function of evolutionary algorithm for optimization of car park space / Ahmad Syahir Ab. Aziz by Ab. Aziz, Ahmad Syahir

    Published 2017
    “…Genetic algorithm is chosen for the development of the prototype to prove that genetic algorithm is the best technique to implement for optimization. …”
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    Thesis
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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
    “…An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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    Final Year Project / Dissertation / Thesis
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  5. 5
    The Anglerfish algorithm: a derivation of randomized incremental construction technique for solving the traveling salesman problem

    The Anglerfish algorithm: a derivation of randomized incremental construction technique for solving the traveling salesman problem by Pook, Mei Foong, Ramlan, Effirul Ikhwan

    Published 2019
    “…The combination of possible solutions are rather vast and often overwhelms the limited computational power. Smart algorithms have been developed to address this issue. …”
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  6. 6
    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree

    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree by Hasliza, A. Rahim@Samsuddin, Ab Rahman, A. A H, Andaljayalakshmi, G., R. Badlishah, Ahmad, Wan Nur Suryani Firuz, Wan Ariffin

    Published 2009
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  7. 7
    Modeling Of Curves And Surfaces Using Ght-Bernstein Basis Functions And Using Optimization Methods To Construct Developable Surfaces

    Modeling Of Curves And Surfaces Using Ght-Bernstein Basis Functions And Using Optimization Methods To Construct Developable Surfaces by Bibi, Samia

    Published 2024
    “…The developability degree of the surface is the objective function in optimization techniques. …”
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  8. 8
    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…The algorithm developed in this thesis contains three sub-algorithms. …”
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  9. 9
    Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences

    Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences by Rajesvary Rajoo R., Salam R.A.

    Published 2024
    journal::journal article
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  10. 10
    Development of a scheduling tool for constructing a Malaysian school timetable using genetic algorithms / Salihin Farag Shoeeb

    Development of a scheduling tool for constructing a Malaysian school timetable using genetic algorithms / Salihin Farag Shoeeb by Salihin Farag , Shoeeb

    Published 2003
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  11. 11
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  12. 12
    DEVELOPMENT OF A MULTI-OBJECTIVE OPTIMZATION FRAMEWORK FOR INDUSTRIAL PROCESSES

    DEVELOPMENT OF A MULTI-OBJECTIVE OPTIMZATION FRAMEWORK FOR INDUSTRIAL PROCESSES by GANESAN, TIMOTHY

    Published 2014
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  13. 13
    Optimizing optimal path trace back for Smith-Waterman algorithm using structural modelling technique

    Optimizing optimal path trace back for Smith-Waterman algorithm using structural modelling technique by Saliman, Nur Farah Ain

    Published 2012
    “…Therefore, the second design is the best approach in optimizing the optimal path trace back for Smith Waterman algorithm. …”
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    Student Project
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  14. 14
    Process Planning Optimization In Reconfigurable Manufacturing Systems

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…Therefore, this study explores how to model reconfigurable manufacturing activities in an optimization perspective and how to develop and select appropriate non-conventional optimization techniques for reconfigurable process planning.In this study, a new approach to modeling Manufacturing Process Planning Optimization (MPPO) was developed by extending the concept of manufacturing optimization through a decoupled optimization method. …”
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  15. 15
    Optimized feature construction methods for data summarizations of relational data

    Optimized feature construction methods for data summarizations of relational data by Sze, Florence Sia Fui

    Published 2014
    “…The proposed framework involves the application of genetic algorithm which incorporates several feature scoring measures to optimize the process of feature construction. …”
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  16. 16
    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree

    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree by Rahim At Samsuddin, H. A., Ab. Rahman, A. A. H., Andaljayalakshmi, G., Ahmad, R. B.

    Published 2008
    “…This algorithm demonstrates that SSGA converges to the optimal result faster than SGA and AGA. …”
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  17. 17
    Web-based RIG performance reporting system using interactive visualization techniques / Amir Hambaly Nasaruddin

    Web-based RIG performance reporting system using interactive visualization techniques / Amir Hambaly Nasaruddin by Nasaruddin, Amir Hambaly

    Published 2019
    “…D3.js is used as a technology to visualize the result in interactive form or dynamic visualization which is a JavaScript library and Python is a language to program the system. …”
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  18. 18
    Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm

    Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm by Nukman, Y., Hassan, M.A., Harizam, M.Z.

    Published 2013
    “…In some cases, the prediction errors of Taguchi ANN model was larger than 10 even with Levenberg Marquardt training algorithm. To overcome such problem, a hybrid genetic algorithm-based Taguchi ANN (GA-Taguchi ANN) has been developed. …”
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  19. 19
    A Stepper Motor Design Optimization Using

    A Stepper Motor Design Optimization Using by Wong, Chin Wei

    Published 2005
    “…There is a need to fill this void in the area of small-motor design, and develop a program using Genetic Algorithms (GAs) as an approach to achieve optimization. …”
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    Monograph
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  20. 20
    Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems

    Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems by Nazif, Habibeh

    Published 2010
    “…A Genetic Algorithm is successful in generating near -optimal solutions if it is able to produce o®spring during crossover that is better than the parent solutions. …”
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