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  1. 1
    Hybrid Intelligent Water Drops Algorithm For Examination Timetabling Problem

    Hybrid Intelligent Water Drops Algorithm For Examination Timetabling Problem by Bashar A.Aldeeb, Mohammed Azmi Al-Betar, Norita Md Norwawi, Khalid A.Alissa, Mutasem K.Alsmadi, Ayman A.Hazaymeh, Malek Alzaqebah

    Published 2024
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  2. 2
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. ANN is a computer-based simulation of the living nervous system which works quite differently from conventional programming. …”
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  3. 3
    Vision Based Multi Sensor Feedback System For Robot System With Intelligent

    Vision Based Multi Sensor Feedback System For Robot System With Intelligent by Syed Mohamad Shazali, Syed Abdul Hamid

    Published 2009
    “…This research studies the machine vision system and how it may be integrated to assist a robot system with artificial intelligent (Al). This research focuses on building a vision based feedback system for robotics application that consists of image processor and two vision-based sensor devices. …”
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  4. 4
    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems

    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

    Published 2024
    thesis::doctoral thesis
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  5. 5
    Artificial intelligence technique in solving nano-process parameter optimization problem / Norlina Mohd Sabri...[et al.]

    Artificial intelligence technique in solving nano-process parameter optimization problem / Norlina Mohd Sabri...[et al.] by Mohd Sabri, Norlina, Puteh, Mazidah, Md Sin, Nor Diyana

    Published 2017
    “…Based on the results, GA has shown the best performance compared to PSO and GSA in terms of the fitness value and processing time. …”
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  6. 6
    Development of Intelligent Leak Detection System Based on Artificial Pressure Transient Signal Using Integrated Kurtosis-Based Algorithm for Z-Filter Technique (I-Kaz) / Hanafi.M.Yusop...[et al.]

    Development of Intelligent Leak Detection System Based on Artificial Pressure Transient Signal Using Integrated Kurtosis-Based Algorithm for Z-Filter Technique (I-Kaz) / Hanafi.M.Y... by M.Yusop, Hanafi, Ghazali, M.F., M.Yusof, M.F., W.Hamat, W.S.

    Published 2017
    “…However, this method has the difficulty in selecting the suitable IMF for the next data post-processing method which is Hilbert Transform (HT). To develop intelligent leak detection system through Hilbert-Huang Transform (HHT) analysis, the selection for IMF must be automated and self-decision making process through the system. …”
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  7. 7
    Second compression for pixelated images under edge-based compression algorithms: JPEG-LS as an example

    Second compression for pixelated images under edge-based compression algorithms: JPEG-LS as an example by Al-Khayyat, Kamal, Alshaikhli, Imad Fakhri Taha, Al-Hagery, Mohammed

    Published 2021
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  8. 8
    Dynamic traffic light sequence algorithm using RFID

    Dynamic traffic light sequence algorithm using RFID by Al-Khateeb, Khalid A. Saeed, Johari, Jaiz A. Y, Al-Khateeb, Wajdi Fawzi Mohammed

    Published 2008
    “…Results: The simulation has shown that, the dynamic sequence algorithm has the ability to intelligently adjust itself even with the presence of some extreme cases. …”
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  9. 9
    Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment

    Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S.

    Published 2024
    “…In this paper, the optimised Apriori association rule algorithm is used as technical support to realise the function of interlocking fault diagnosis in the intelligent fault diagnosis system module. …”
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  10. 10
    Computational dynamic support model for social support assignments around stressed individuals among graduate students

    Computational dynamic support model for social support assignments around stressed individuals among graduate students by Al-Shorman, Roqia Rateb

    Published 2020
    “…Later, the dynamic configuration algorithm was designed to utilize possible support assignments based on support provision requirements. …”
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  11. 11
    Hybrid intelligent approach for network intrusion detection

    Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

    Published 2015
    “…Clustering is the last step of processing before classification has been performed, using k-means algorithm. …”
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  12. 12
    Design and Development of Artificial Intelligence (Al)-Based Desicion Support System For Manufacturing Applications

    Design and Development of Artificial Intelligence (Al)-Based Desicion Support System For Manufacturing Applications by Lim , Chee Peng

    Published 2016
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  13. 13
    An Intelligent of ANN towards agarwood oil compounds pre-processing based on stepwise regression method to improve the oil quality / Noratikah Zawani Mahabob … [et al.]

    An Intelligent of ANN towards agarwood oil compounds pre-processing based on stepwise regression method to improve the oil quality / Noratikah Zawani Mahabob … [et al.] by Mahabob, Noratikah Zawani, Mohd Amidon, Aqib Fawwaz, Mohd Yusoff, Zakiah, Ismail, Nurlaila, Taib, Mohd Nasir

    Published 2021
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  14. 14
    Hybrid Neural Networks and Genetic Algorithm for Fault Detection and Diagnosis of a Plant

    Hybrid Neural Networks and Genetic Algorithm for Fault Detection and Diagnosis of a Plant by Al-Neami, F. B., Al-Kayiem, Hussain H.

    Published 2008
    “…The recent work presents a new method of fault diagnosis based on artificial neural networks and genetic algorithms. …”
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  15. 15
    Hidden markov model for decision making among heterogeneous systems in intelligent building

    Hidden markov model for decision making among heterogeneous systems in intelligent building by Abba, Babakura

    Published 2014
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  16. 16
    An Intelligent of ANN towards agarwood oil compounds pre-processing based on stepwise regression method to improve the oil quality / Noratikah Zawani Mahabob … [et al.]

    An Intelligent of ANN towards agarwood oil compounds pre-processing based on stepwise regression method to improve the oil quality / Noratikah Zawani Mahabob … [et al.] by Mahabob, Noratikah Zawani, Mohd Amidon, Aqib Fawwaz, Mohd Yusoff, Zakiah, Ismail, Nurlaila, Taib, Mohd Nasir

    Published 2021
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  17. 17
    Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs

    Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs by F. Al-dolaimy, F. Al-dolaimy, Rabei Raad Al, Rabei Raad Al, Noor Nabeel, Noor Nabeel, Wisam Subhi Al-Dayyeni4, Wisam Subhi Al-Dayyeni4, Hashim Abbas, Fatima, Muhi Hariz, Hussein, A Mostafa, Salama, Jubair, Mohammed Ahmed

    Published 2023
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  18. 18
    Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs

    Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs by F. Al-dolaimy, F. Al-dolaimy, Rabei Raad Ali, Rabei Raad Ali, Noor Nabeel, Noor Nabeel, Wisam Subhi Al-Dayyeni, Wisam Subhi Al-Dayyeni, Hashim Abbas, Fatima, Muhi Hariz, Hussein, A Mostafa, Salama, Jubair, Mohammed Ahmed

    Published 2023
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  19. 19
    Boosting and bagging classification for computer science journal

    Boosting and bagging classification for computer science journal by Wibawa, Aji Prasetya, Putri, Nastiti Susetyo Fanany, Al Rasyid, Harits, Nafalski, Andrew, Hashim, Ummi Rabaah

    Published 2023
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  20. 20
    Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs

    Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs by F. Al-dolaimy, F. Al-dolaimy, Rabei Raad Ali, Rabei Raad Ali, Noor Nabeel, Noor Nabeel

    Published 2023
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