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  1. 1
    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter

    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

    Published 2019
    “…It does not consider the LACE algorithm implemented in huge number of server in one Cloud datacenter. …”
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  2. 2
    Network game (Literati) / Chung Mei Kuen

    Network game (Literati) / Chung Mei Kuen by Chung, Mei Kuen

    Published 2003
    “…This thesis steps towards developing a networked game, Literati game system that supporting two players at one time. …”
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  3. 3
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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  4. 4
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  5. 5
    Logic Programming In Radial Basis Function Neural Networks

    Logic Programming In Radial Basis Function Neural Networks by Hamadneh, Nawaf

    Published 2013
    “…The first technique is to encode the logic programming in radial basis function neural networks. …”
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  6. 6
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  7. 7
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  8. 8
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  9. 9
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  10. 10
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  11. 11
    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO)

    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO) by Mohd Erwan Mazalan

    Published 2022
    “…The minimization of system execution and transfer time in the proposed algorithm are considered as objective functions. The experimental testing of the proposed algorithm are considered as objective functions. …”
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    Academic Exercise
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  12. 12
    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
    “…The circuits have been designed by proteus, the microcontrollers have been programmed by micro C, and the Graphical User Interface (GUI) has been implemented in Java. Few by electronic components such as RFID, multiplexer, XBee, and servo motors have been used to realize the system. …”
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  13. 13
    Design & Development of a Robotic System Using LEGO Mindstorm

    Design & Development of a Robotic System Using LEGO Mindstorm by Abd Manap, Nurulfajar, Md Salim, Sani Irwan, Haron, Nor Zaidi

    Published 2006
    “…The system is capable in operating an off-line programming method, starting from its programming sequences until robotic implementation of the program. During early stages, the research is emphasis more towards designing a robotic system using RoboLab software and C++ programming language. …”
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    Conference or Workshop Item
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  14. 14
    A combined filter line search and trust region method for nonlinear programming

    A combined filter line search and trust region method for nonlinear programming by Chin, Choong Ming, Halim, Abdul, Rashid, A. H. A., Nor, K. M.

    Published 2006
    “…The proposed technique first solve a sequence of quadratic programming subproblems via line search strategy and to induce global convergence, trial points are accepted provided there is a sufficient decrease in the objective function or constraints violation function. …”
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  15. 15
    Enhancing Performance of Batik SMEs through Cleaner Production Adoption: Insights from Clustering Algorithm Analysis

    Enhancing Performance of Batik SMEs through Cleaner Production Adoption: Insights from Clustering Algorithm Analysis by Achmad, Fandi, Zulkarnain, Ibnu, Rumanti, Augustina Asih, Wiratmadja, Iwan Inrawan, Shuhidan, Shuhaida Mohamed

    Published 2025
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  16. 16
    A Constraint Programming-based Genetic Algorithm (CPGA) for Capacity Output Optimization

    A Constraint Programming-based Genetic Algorithm (CPGA) for Capacity Output Optimization by Ean, Kate Nee Goh, Jeng, Feng Chin, Wei, Ping Loh, Chea, Ling Tan

    Published 2014
    “…Design/methodology/approach: In the first stage, constraint programming defining the relationships between variables was formulated into the objective function. …”
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  17. 17
    Analytical Approach for Linear Programming Using Barrier and Penalty Function Methods

    Analytical Approach for Linear Programming Using Barrier and Penalty Function Methods by Moengin, Parwadi

    Published 2003
    “…Thus, in this research we study and analyze how the behavior and performance of barrier functions and penalty functions methods for solving the linear programming problems. …”
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  18. 18
    Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar

    Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar by Mohamed Azhar, Nur Afiqah

    Published 2019
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  19. 19
    Online Programming Judge System (UOJ)

    Online Programming Judge System (UOJ) by Tran , Quang Trung

    Published 2013
    “…The system has the function to judge programming code by evaluating the output that the program produced. …”
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  20. 20
    A new meta heuristic evolutionary programming (NMEP) in optimizing economic energy dispatch

    A new meta heuristic evolutionary programming (NMEP) in optimizing economic energy dispatch by Mohamad Ridzuan, Mohamad Radzi, Hassan, Elia Erwani, Abdullah, Abdul Rahim, Bahaman, Nazrulazhar, Abdul Kadir, Aida Fazliana

    Published 2016
    “…The proposed optimization algorithm, namely New Meta-Heuristic Evolutionary Programming (NMEP) algorithm is followed to Meta-Heuristic Evolutionary Programming (Meta-EP) approach with some modification where the cloning process embedded as a significant progress during the implementation. …”
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