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  1. 1
    Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm

    Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm by ,, Dwi Pebrianti, Ann Ayop azmi, Nurnajmi Qasrina, Bayuaji, Luhur, Suarin, Nur Aisyah Syafinaz, ,, Muhammad Syafrullah

    Published 2022
    “…Three different optimization algorithms which are Bat Algorithm (BA), Bat Algorithm with Mutation (BAM) and Extended Bat Algorithm (EBA) are implemented to optimize the value of PID controller gain for wheel mobile robot. …”
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  2. 2
    PID controller design for mobile robot using Bat Algorithm with Mutation (BAM)

    PID controller design for mobile robot using Bat Algorithm with Mutation (BAM) by Pebrianti, Dwi, Indra, Riyanto, Bayuaji, Luhur, Muhammad Syafrullah, ., Arumgam, Yogesvaran, Nurnajmin Qasrina, Ann

    Published 2019
    “…Here, an optimization algorithm called Bat Algorithm with Mutation (BAM) is proposed to optimize the value of PID controller gain for mobile robot. …”
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  3. 3
    Multi-Robot Learning with Bat Algorithm With Mutation (Bam)

    Multi-Robot Learning with Bat Algorithm With Mutation (Bam) by Chandrathevan, Sathiamurthy

    Published 2022
    “…BAT algorithm is implemented to achieve the target. …”
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  4. 4
    Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali

    Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali by Ihsan , Ali

    Published 2024
    “…To address relay node selection and data scheduling issues, Energy-Efficient Scheduling (EES) and Energy-Efficient Un-Scheduling (EEUS) methods have been introduced using the Improved Discrete Bat Algorithm (IDBA) along with the Adaptive Warshal Floyd algorithm (AWF). …”
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  5. 5
    An algorithm for Elliott Waves pattern detection

    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70 proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns. …”
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  6. 6
    An algorithm for Elliott Waves pattern detection

    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70 proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns. …”
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  7. 7
    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff

    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

    Published 2017
    “…Thus, it can be concluded that QEEA algorithm is the most energy efficient and the best candidate for provisioning the QoS for the real time (RT) and non-real time (NRT) applications.…”
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  8. 8
    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks

    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

    Published 2025
    thesis::doctoral thesis
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  9. 9
    Market prices trend forecasting supported by Elliott Wave's theory

    Market prices trend forecasting supported by Elliott Wave's theory by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2017
    “…The trend prediction is supported by application of recognized Elliot waves which was performed by custom developed algorithm based on available knowledge about the patterns. …”
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  10. 10
    Machine learning approach for stress detection based on alpha-beta and theta-beta ratios of EEG signals

    Machine learning approach for stress detection based on alpha-beta and theta-beta ratios of EEG signals by Altaf, Hunain, Ibrahim, Siti Noorjannah, Mohd Azmin, Nor Fadhillah, Asnawi, Ani Liza, Walid, Balqis Hanisah, Harun, Noor Hasmiza

    Published 2021
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  11. 11
    Water wave optimization with deep learning driven smart grid stability prediction

    Water wave optimization with deep learning driven smart grid stability prediction by Mustafa Hilal, Anwer, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, Alamgeer, Mohammad, K. Nour, Mohamed, Abdelrahman, Anas, Motwakel, Abdelwahed

    Published 2022
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  12. 12
    A review of wave-net identical learning & filling-in in a decomposition space of (JPG-JPEG) sampled images

    A review of wave-net identical learning & filling-in in a decomposition space of (JPG-JPEG) sampled images by Al-Azzawi, Alaa Khamees, Saripan, M. Iqbal, Jantan, Adznan, O. K. Rahmat, Rahmita Wirza

    Published 2010
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  13. 13
    Machine learning in botda fibre sensor for distributed temperature measurement

    Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

    Published 2023
    text::Thesis
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  14. 14
    Neural network approach of harmonics detection

    Neural network approach of harmonics detection by Zin, A.A.M, Rokonuzzaman, M., Shaibon, H., Lo, K.I.

    Published 1998
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  15. 15
    Selective opposition based constrained barnacle mating optimization: Theory and applications

    Selective opposition based constrained barnacle mating optimization: Theory and applications by Ahmed, Marzia, Mohd Herwan, Sulaiman, Hassan, Md. Maruf, Rahaman, Md. Atikur, Abdullah, Masuk

    Published 2024
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  16. 16
    Detection of Corona Faults in Switchgear by Using 1D-CNN, LSTM, and 1D-CNN-LSTM Methods

    Detection of Corona Faults in Switchgear by Using 1D-CNN, LSTM, and 1D-CNN-LSTM Methods by Mohammed Alsumaidaee Y.A., Yaw C.T., Koh S.P., Tiong S.K., Chen C.P., Yusaf T., Abdalla A.N., Ali K., Raj A.A.

    Published 2024
    “…Recent years have seen the successful use of Deep Learning (DL) applications for corona and non-corona detection, owing to their autonomous feature learning capability. …”
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  17. 17
    Joint optimization of resources allocation for quality of service aware next-generation heterogeneous cellular networks / Hayder Faeq Rasool Alhashimi

    Joint optimization of resources allocation for quality of service aware next-generation heterogeneous cellular networks / Hayder Faeq Rasool Alhashimi by Hayder Faeq Rasool , Alhashimi

    Published 2025
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  18. 18
    Access control and classifier-based blockchain technology in e-healthcare applications

    Access control and classifier-based blockchain technology in e-healthcare applications by Maseleno A., Hashim W., Perumal E., Ilayaraja M., Shankar K.

    Published 2023
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  19. 19
    Bayesian Network Classifiers for Damage Detection in Engineering Material

    Bayesian Network Classifiers for Damage Detection in Engineering Material by Mohamed Addin, Addin Osman

    Published 2007
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  20. 20
    Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey

    Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey by Ukasyah Mahamod, Ibraheem Shayea, Hafizal Mohamad, Marinah Othman, Fauzun Abdullah Asuhaimi

    Published 2024
    journal::journal article
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