يعرض 61 - 80 نتائج من 609 نتيجة بحث عن '(( data learning algorithm ) OR ((( develop based algorithm ) OR ( element data algorithm ))))*', وقت الاستعلام: 0.12s تنقيح النتائج
  1. 61

    Using machine learning algorithm for detection of cyber-attacks in cyber physical systems حسب Almajed, Rasha

    منشور في 2022
    "…We begin a process to cleaning up the data in the CPS database by applying normalization to eliminate errors and duplication. …"
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    Online Fuzzy Logic Base Algorithm for Electricity Price Prediction حسب Albayed, Moamin J.

    منشور في 2017
    "…The proposed algorithm was developed and hosted in a utility server (U-server). …"
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    article
  7. 67
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    Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System حسب Abualigah, Laith

    منشور في 2023
    "…This study proposes a novel approach for designing a fractional order proportional-integral-derivative (FOPID) controller that utilizes a modified elite opposition-based artificial hummingbird algorithm (m-AHA) for optimal parameter tuning. …"
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  9. 69
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    Enhancing Personalized Learning Experiences through AI-driven Analysis of xAPI Data حسب ODEH, HANEEN

    منشور في 2024
    "…The Experience API (xAPI) provides a comprehensive mechanism to document all types of learning interactions, storing this stream of data into the Learning Record Store (LRS). …"
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  11. 71

    The buffered work-pool approach for search-tree based optimization algorithms حسب Abu-Khzam, Faisal N.

    منشور في 2017
    "…This new trend has been motivated by hardness of approximation results that appeared in the last decade, and has taken a great boost by the emergence of parameterized complexity theory. Exact algorithms often follow the classical search-tree based recursive backtracking strategy. …"
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    conferenceObject
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    XBeGene: Scalable XML Documents Generator by Example Based on Real Data حسب Harazaki, Manami

    منشور في 2012
    "…XML datasets of various sizes and properties are needed to evaluate the correctness and efficiency of XML-based algorithms and applications. While several downloadable datasets can be found online, these are predefined by system experts and might not be suitable to evaluate every algorithm. …"
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    conferenceObject
  15. 75

    Predict Student Success and Performance factors by analyzing educational data using data mining techniques حسب ATIF, MUHAMMAD

    منشور في 2022
    "…The research study is performed as experimental analysis and develop models from nine machine learning algorithms including KNN, Naïve Bayes, SVM, Logistic regression, Decision Tree, Random forest, Adaboost, Bagging Classifier, and voting Classifier. …"
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  16. 76

    Nonlinear analysis of shell structures using image processing and machine learning حسب M.S. Nashed (16392961)

    منشور في 2023
    "…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …"
  17. 77

    A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network حسب Xiaofang Pan (1895950)

    منشور في 2019
    "…Featuring the capability of learning the correlations of time-series data, the proposed deep learning method is well-suited for extracting the valuable transient feature contained in the very beginning of the response curve. …"
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    The effects of data balancing approaches: A case study حسب Paul Mooijman (4453189)

    منشور في 2023
    "…<p dir="ltr">Imbalanced datasets affect the performance of machine learning algorithms adversely. To cope with this problem, several resampling methods have been developed recently. …"
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    The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs حسب Muhammad Kashif (3923483)

    منشور في 2023
    "…However, the integration of quantum computing and machine learning poses several challenges. One of the prominent challenges lies in the presence of barren plateaus (BP) in QML algorithms, particularly in quantum neural networks (QNNs). …"