Search Results - (( its applications learning algorithm ) OR ( wave application during algorithm ))

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    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. …”
    Article
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    Random traveling wave pulse coupled oscillator (RTWPCO) algorithm of energy-efficient wireless sensor networks by Al-Mekhlafi, Zeyad Ghaleb Aqlan, Mohd Hanapi, Zurina, Othman, Mohamed, Ahmad Zukarnain, Zuriati, Shamsan Saleh, Ahmed M.

    Published 2018
    “…To avert this problem, this study proposes a new mechanism called random traveling wave pulse-coupled oscillator algorithm, which is a self-organizing technique for energy-efficient wireless sensor networks using the phase-locking traveling wave pulse-coupled oscillator and random method on anti-phase of the pulse-coupled oscillator model. …”
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    Article
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    Development of an automated detector and counter for bagworm census by Ahmad, Mohd Najib

    Published 2020
    “…There are several recommendations from this study that have been suggested including the use of hyperspectral imaging to detect bagworms, application of radio frequency to detect live bagworms, open system detection of the bagworms, application of pseudo colour concept and method to detect early stage of bagworm attack.…”
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    Thesis
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    A modified generalized RBF model with EM-based learning algorithm for medical applications by Ma, Li Ya, Abdul Rahman, Abdul Wahab, Quek, Chai

    Published 2006
    “…Radial Basis Function (RBF) has been widely used in different fields, due to its fast learning and interpretability of its solution. …”
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    Proceeding Paper
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    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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    Thesis
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    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…Two main improvements were included into the original SSA algorithm to alleviate its drawbacks and adapt it for feature selection problems. …”
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    Article
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    Active force control with iterative learning control algorithm for a vehicle suspension by Rosmazi, Rosli

    Published 2013
    “…The research focuses on the application of an active force control (AFC) strategy with iterative learning control (ILC) algorithms to compensate for the various introduced road profiles or 'disturbances' in a quarter car suspension system as an improvement to ride comfort performance. …”
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    Thesis
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    Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding by Mahmoud, Omer, Anwar, Farhat, Salami, Momoh Jimoh Emiyoka

    Published 2007
    “…The essence of this study is to investigate the most efficient and effective training methods for use in image compression and its subsequent applications. The obtained results show that the Quasi-Newton based algorithm has better performance as compared to the other two algorithms.…”
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    Article
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    Machine learning: tasks, modern day applications and challenges by Aljuaid, Lamyaa Zaed, Koh, Tieng Wei, Sharif, Khaironi Yatim

    Published 2019
    “…Machine learning algorithms learned from available data. Further, this learning laid the foundation to develop AI for the various systems around us. …”
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    Article
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