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  1. 1
    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
    “…TCP factors and a weighted fitness function are also used for test case optimisation. …”
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  2. 2
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  3. 3
    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs

    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

    Published 2019
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  4. 4
    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices

    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2013
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  5. 5
    Real-Time Video Processing Using Native Programming on Android Platform

    Real-Time Video Processing Using Native Programming on Android Platform by Saipullah, Khairul Muzzammil

    Published 2012
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  6. 6
    Detection and extraction features for signatures images via different techniques

    Detection and extraction features for signatures images via different techniques by Fatma Susilawati, M., Alsuhimat, F.M., Iqtait, M.

    Published 2019
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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 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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  8. 8
    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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  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 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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  11. 11
    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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  12. 12
    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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  13. 13
    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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  14. 14
    An approach for cross-site scripting detection and removal based on genetic algorithms.

    An approach for cross-site scripting detection and removal based on genetic algorithms. by Hydara, Isatou, Md Sultan, Abu Bakar, Zulzalil, Hazura, Admodisastro, Novia

    Published 2014
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  15. 15
    Fitness value based evolution algorithm approach for text steganalysis model

    Fitness value based evolution algorithm approach for text steganalysis model by Din, Roshidi, Samsudin, Azman, Tuan Muda, Tuan Zalizam, Lertkrai, P., Amphawan, Angela, Omar, Mohd Nizam

    Published 2013
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  16. 16
    Cross-site scripting detection based on an enhanced genetic algorithm

    Cross-site scripting detection based on an enhanced genetic algorithm by Hydara, Isatou, Md Sultan, Abu Bakar, Zulzalil, Hazura, Admodisastro, Novia Indriaty

    Published 2015
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  17. 17
    Identification of microcalcification in mammographic images / Noor Azliza Abdul Shauti

    Identification of microcalcification in mammographic images / Noor Azliza Abdul Shauti by Abdul Shauti, Noor Azliza

    Published 2008
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  18. 18
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
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  19. 19
    Text steganalysis using evolution algorithm approach

    Text steganalysis using evolution algorithm approach by Din, Roshidi, Tuan Muda, Tuan Zalizam, Lertkrai, Puriwat, Omar, Mohd Nizam, Amphawan, Angela, Aziz, Fakhrul Anuar

    Published 2012
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  20. 20
    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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