يعرض 1 - 20 نتائج من 33 نتيجة بحث عن '(( python model predictive ) OR ( python time implementation ))~', وقت الاستعلام: 0.25s تنقيح النتائج
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    Prediction accuracy analysis over time steps. حسب Mohanad Faeq Ali (21354273)

    منشور في 2025
    "…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …"
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    Five Operator Lattice Simulation حسب James McDaniel (22522571)

    منشور في 2025
    "…</p><p dir="ltr"><b>License:</b> CC BY 4.0 <b>Keywords:</b> Five-Operator Lattice; Consciousness; Complex Systems; Cognitive Architecture; Predictive Processing; Python Simulation; Applied Mathematics.…"
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    Prediction accuracy on varying attack types. حسب Mohanad Faeq Ali (21354273)

    منشور في 2025
    "…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …"
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    Graphical abstract of HCAP. حسب Mohanad Faeq Ali (21354273)

    منشور في 2025
    "…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …"
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    Recall analysis. حسب Mohanad Faeq Ali (21354273)

    منشور في 2025
    "…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …"
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    Convergence rate analysis. حسب Mohanad Faeq Ali (21354273)

    منشور في 2025
    "…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …"
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    Computational efficiency. حسب Mohanad Faeq Ali (21354273)

    منشور في 2025
    "…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …"
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    Analysis of IoMT data sources. حسب Mohanad Faeq Ali (21354273)

    منشور في 2025
    "…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …"
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    <b> </b> Precision analysis. حسب Mohanad Faeq Ali (21354273)

    منشور في 2025
    "…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …"
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    Impact of cyberattack types on IoMT devices. حسب Mohanad Faeq Ali (21354273)

    منشور في 2025
    "…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …"
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    The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" حسب FirstName LastName (20554465)

    منشور في 2025
    "…</p><p dir="ltr"><i>cd 1point2dem/CIPrediction</i></p><p dir="ltr"><i>python -u point_prediction.py --model [GCN|ChebNet|GATNet]</i></p><h3>step 4: Parallel computation</h3><p dir="ltr">This step uses the trained models to optimize parallel computation. …"
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    The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" حسب FirstName LastName (20554465)

    منشور في 2025
    "…</p><p dir="ltr"><i>cd 1point2dem/CIPrediction</i></p><p dir="ltr"><i>python -u point_prediction.py --model [GCN|ChebNet|GATNet]</i></p><h3>step 4: Parallel computation</h3><p dir="ltr">This step uses the trained models to optimize parallel computation. …"
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    Summary of Tourism Dataset. حسب Jing Zhang (23775)

    منشور في 2025
    "…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …"
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    Segment-wise Spending Analysis. حسب Jing Zhang (23775)

    منشور في 2025
    "…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …"