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  1. 1

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
    “…The outcome of this study will add to the body of knowledge the most important and recent proposed solutions to mitigate SQL injection attack, in particular those based on machine learning algorithm…”
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    Article
  2. 2

    Exploration of machine learning forecasting methods in M4 competition / Muhammad Halim Hamdan and Shuzlina Abdul-Rahman by Hamdan, Muhammad Halim, Abdul-Rahman, Shuzlina

    Published 2021
    “…Each technique was replicated, trained and tested accordingly. M4 competition dataset was used in this research, with 100,000 time series data and multiple data frequency, which is enough to replicate the real-world situation. …”
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  3. 3

    Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data by Fanos, Ali Mutar, Pradhan, Biswajeet, Mansor, Shattri, Md Yusoff, Zainuddin, Abdullah, Ahmad Fikri, Jung, Hyung Sup

    Published 2019
    “…The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. …”
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    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

    Published 2024
    “…Although the swmcan algorithm solves the noise problem in multi-view data, its initial and final graphs are independent and cannot learn from each other. …”
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    Thesis
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    Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018?2023) by Hosseini E., Al-Ghaili A.M., Kadir D.H., Gunasekaran S.S., Ahmed A.N., Jamil N., Deveci M., Razali R.A.

    Published 2025
    “…This paper provides a comprehensive review spanning 2018 to 2023, examining the integration of meta-heuristic algorithms within deep learning frameworks for energy applications. …”
    Review
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    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

    Published 2023
    “…Generally, medical data is considered high-dimensional and complex data that contains many irrelevant and redundant features. …”
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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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    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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    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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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
    “…Many fields such as data science, data mining suffered from the rapid growth of data volume and high data dimensionality. …”
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    Comparative study of machine learning algorithms in data classification by Tan, Kai Jun

    Published 2025
    “…The results will help with real-world data mining applications of machine learning and be a useful guide for further study and practical applications.…”
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    Final Year Project / Dissertation / Thesis
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    Securing IoT networks using machine learning-resistant physical unclonable functions (PUFs) on edge devices by Sheikh, Abdul Manan, Islam, Md. Rafiqul, Habaebi, Mohamed Hadi, Zabidi, Suriza Ahmad, Najeeb, Athaur Rahman, Baloch, Mazhar

    Published 2026
    “…The Internet of Things (IoT) has transformed global connectivity by linking people, smart devices, and data. However, as the number of connected devices continues to grow, ensuring secure data transmission and communication has become increasingly challenging. …”
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    Article
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