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  1. 1
    An enhancement of multi-factor weighted approach technique in prioritizing test cases by comparing similarity distance

    An enhancement of multi-factor weighted approach technique in prioritizing test cases by comparing similarity distance by Al-Shaibani, Alaa Alrhman Mohammed Raweh, Ahmad, Johanna, Hassan, Rohayanti, Baharom, Salmi, Antari, Dwinta Suci

    Published 2025
    “…Therefore, numerous factors and techniques have been used to optimize the prioritization process. …”
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  2. 2
    A heuristics approach for classroom scheduling using genetic algorithm technique

    A heuristics approach for classroom scheduling using genetic algorithm technique by Ahmad, Izah R., Sufahani, Suliadi, Ali, Maselan, Mohd Razali, Siti Noor Asyikin

    Published 2017
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  3. 3
    Optimize class time tabling by using genetic algorithm technique in UTHM

    Optimize class time tabling by using genetic algorithm technique in UTHM by Ahmad, Izah Rafidah

    Published 2019
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  4. 4
    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT

    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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  5. 5
    Hybrid genetic algorithm for improving fault localization

    Hybrid genetic algorithm for improving fault localization by Mahamad Zakaria, Muhammad Luqman, Sharif, Khaironi Yatim, Abd Ghani, Abdul Azim, Koh, Tieng Wei, Zulzalil, Hazura

    Published 2018
    “…Genetic algorithm (GA) is well known in finding an optimal solution to a problem while local search is capable of removing duplication. …”
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  6. 6
    Parallel distributed genetic algorithm development based on microcontrollers framework

    Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

    Published 2023
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  7. 7
    Examination timetabling using genetic algorithm case study: KUiTTHO

    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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  8. 8
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
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  9. 9
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Recently, various techniques based on different algorithms have been developed. …”
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  10. 10
    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO

    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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  11. 11
    Improving Class Timetabling using Genetic Algorithm

    Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

    Published 2006
    “…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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  12. 12
    SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment

    SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment by Murad, Saydul Akbar, Zafril Rizal, M. Azmi, Muzahid, Abu Jafar Md, Bhuiyan, Md Khairul Bashar, Saib, Md, Rahimi, Nick, Prottasha, Nusrat Jahan, Bairagi, Anupam Kumar

    Published 2024
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  13. 13
    Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure

    Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure by Ramasamy, Chitra, Zolkepli, Maslina

    Published 2019
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  14. 14
    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
    “…This research employed a modified version of the Design Science Research Methodology (DSRM), streamlined into five stages: problem identification, theoretical study, framework development, evaluation, and reporting. The developed framework, grounded in fault-based testing theory, comprises three key components: inputs, prioritization factors, and a prioritization algorithm. …”
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  15. 15
    A holistic review on artificial intelligence techniques for well placement optimization problem

    A holistic review on artificial intelligence techniques for well placement optimization problem by Islam, J., Vasant, P.M., Negash, B.M., Laruccia, M.B., Myint, M., Watada, J.

    Published 2020
    “…Newly developed optimization algorithms are very efficient and favorable when compared to other established optimization algorithms and in all cases, it has been noticed that hybridization of two or more algorithms works better than stand-alone algorithms. …”
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  16. 16
    An improved diabetes risk prediction framework : An Indonesian case study

    An improved diabetes risk prediction framework : An Indonesian case study by Sutanto, Daniel Hartono

    Published 2018
    “…However,there is the issue of noisy dataset detected as incomplete data and the outlier class problem that affects sampling bias.Existing frameworks were deemed difficult in identifying the critical risk factors of diabetes;some of which were considerably inaccurate and consume substantial computation time.The purpose of this study is to develop a suitable framework for predicting diabetes risks.From a complete blood test,the framework can predict and classify the output of either having diabetes risk or no diabetes risk.A Diabetes Risk Prediction Framework (DRPF) was developed from the literature review and case studies were afterwards conducted in three private hospitals in Semarang.Analyses were conducted to find a suitable component of the framework—due to lack of comparison and analysis on the combination of feature selection and classification algorithm.DRPF comprises four main sections: pre-processing,outlier detection,risk weighting,and learning. …”
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  17. 17
    Reducing Iteration Using Candidate List

    Reducing Iteration Using Candidate List by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

    Published 2008
    “…Their ability as a colony to find paths or routes to the food sources has inspired a newly developed algorithm called Dynamic Ant Colony System 3 Level Updates (DACS3). …”
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  18. 18
    Modified damage location indices in beam-like structure: Analytical study

    Modified damage location indices in beam-like structure: Analytical study by Fayyadh, M.M., Razak, H.A.

    Published 2011
    “…The modified algorithms are able to detect the damage wherever its location, applying even to cases of multi damage locations. …”
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  19. 19
    Development of a Prediction Algorithm using Boosted Decision Trees for Earlier Diagnoses on Obstructive Sleep Apnea

    Development of a Prediction Algorithm using Boosted Decision Trees for Earlier Diagnoses on Obstructive Sleep Apnea by Sim, Doreen Ying Ying

    Published 2018
    “…The developed prediction iv algorithms have been proven to help medical doctors with earlier clinical diagnoses on OSA cases, especially in Malaysia.…”
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  20. 20
    Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm

    Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm by Mohamad Zunnurain Fauzi

    Published 2023
    “…The first case the system will operate without DG installation and the rest of the cases system will operate with single and multiple DG installation with specified power factor. …”
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