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  • Open Access

    ARTICLE

    Optimized Phishing Detection with Recurrent Neural Network and Whale Optimizer Algorithm

    Brij Bhooshan Gupta1,2,3,*, Akshat Gaurav4, Razaz Waheeb Attar5, Varsha Arya6,7, Ahmed Alhomoud8, Kwok Tai Chui9

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4895-4916, 2024, DOI:10.32604/cmc.2024.050815 - 12 September 2024

    Abstract Phishing attacks present a persistent and evolving threat in the cybersecurity land-scape, necessitating the development of more sophisticated detection methods. Traditional machine learning approaches to phishing detection have relied heavily on feature engineering and have often fallen short in adapting to the dynamically changing patterns of phishing Uniform Resource Locator (URLs). Addressing these challenge, we introduce a framework that integrates the sequential data processing strengths of a Recurrent Neural Network (RNN) with the hyperparameter optimization prowess of the Whale Optimization Algorithm (WOA). Our model capitalizes on an extensive Kaggle dataset, featuring over 11,000 URLs, each More >

  • Open Access

    ARTICLE

    Research on Stick-Slip Vibration Suppression Method of Drill String Based on Machine Learning Optimization

    Kanhua Su, Jian Wei*, Meng Li, Hao Li, Wenghao Da, Lang Zhang

    Sound & Vibration, Vol.57, pp. 97-117, 2023, DOI:10.32604/sv.2023.043734 - 14 December 2023

    Abstract During the drilling process, stick-slip vibration of the drill string is mainly caused by the nonlinear friction generated by the contact between the drill bit and the rock. To eliminate the fatigue wear of downhole drilling tools caused by stick-slip vibrations, the Fractional-Order Proportional-Integral-Derivative (FOPID) controller is used to suppress stick-slip vibrations in the drill string. Although the FOPID controller can effectively suppress the drill string stick-slip vibration, its structure is flexible and parameter setting is complicated, so it needs to use the corresponding machine learning algorithm for parameter optimization. Based on the principle of… More > Graphic Abstract

    Research on Stick-Slip Vibration Suppression Method of Drill String Based on Machine Learning Optimization

  • Open Access

    ARTICLE

    An Efficient Machine Learning Based Precoding Algorithm for Millimeter-Wave Massive MIMO

    Waleed Shahjehan1, Abid Ullah1, Syed Waqar Shah1, Ayman A. Aly2, Bassem F. Felemban2, Wonjong Noh3,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5399-5411, 2022, DOI:10.32604/cmc.2022.022034 - 14 January 2022

    Abstract Millimeter wave communication works in the 30–300 GHz frequency range, and can obtain a very high bandwidth, which greatly improves the transmission rate of the communication system and becomes one of the key technologies of fifth-generation (5G). The smaller wavelength of the millimeter wave makes it possible to assemble a large number of antennas in a small aperture. The resulting array gain can compensate for the path loss of the millimeter wave. Utilizing this feature, the millimeter wave massive multiple-input multiple-output (MIMO) system uses a large antenna array at the base station. It enables the… More >

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