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  1. 1
    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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  2. 2
    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation

    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation by Kumar, A., Ridha, S., Ganet, T., Vasant, P., Ilyas, S.U.

    Published 2020
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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
    Recognising Malaysia traffic sign with rain drop disturbance using deep learning

    Recognising Malaysia traffic sign with rain drop disturbance using deep learning by Pang, Wan Chee

    Published 2022
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  7. 7
    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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  8. 8
    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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  9. 9
    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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  10. 10
    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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  11. 11
    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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  12. 12
    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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  13. 13
    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS

    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS by AYOUB MOHAMMED, MOHAMMED ABDALLA

    Published 2011
    “…The ANN model has been developed using resilient back-propagation learning algorithm. …”
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  14. 14
    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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  15. 15
    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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  16. 16
    Development of predictive modeling and deep learning classification of taxi trip tolls

    Development of predictive modeling and deep learning classification of taxi trip tolls by Al-Shoukry, Suhad, M. Jawad, Bushra Jaber, Zalili, Musa, Sabry, Ahmad H.

    Published 2022
    “…Using a classification algorithm, it is possible to extract drop-off and pickup locations from taxi trip data and estimate if the tour would incur tolls. …”
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  17. 17
    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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  18. 18
    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman

    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman by Abdul Rahman, Muhammad Nur Azri Irfan

    Published 2025
    “…The methodology followed a structured three-phase process: The first stage was the collection of a dataset of 5,099 images of 30 different musical instruments of Kaggle, providing variable lighting, angles, or backgrounds, along with preprocessing to standardize the inputs. In the development phase, Convolutional Neural Network model was designed and trained using sophisticated techniques of data augmentation, dropping out and hyperparameter tuning under the supervised learning methodology to increase the performance of the system. …”
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  19. 19
    Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection

    Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection by Ahmed Khan, Fazeel, Abubakar, Adamu

    Published 2024
    “…The data was gathered using real-time packet capturing tools which were then processed and moved with model development using different deep learning algorithms such as, LSTM, MLP, RNN and Autoencoders. …”
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  20. 20
    A comparative study and simulation of object tracking algorithms

    A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

    Published 2020
    “…The algorithms using convolution features and multi-features fusion algorithms have more advantages in tracking accuracy than the algorithm using a single feature, but the tracking speed will also drop rapidly. …”
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