يعرض 1 - 20 نتائج من 27 نتيجة بحث عن '(( primary data guided optimization algorithm ) OR ( binary wave driven optimization algorithm ))*', وقت الاستعلام: 1.16s تنقيح النتائج
  1. 1

    Models’ performance without optimization. حسب Muhammad Usman Tariq (11022141)

    منشور في 2024
    "…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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    Data_Sheet_1_Prediction of patient choice tendency in medical decision-making based on machine learning algorithm.pdf حسب Yuwen Lyu (14330781)

    منشور في 2023
    "…Objective<p>Machine learning (ML) algorithms, as an early branch of artificial intelligence technology, can effectively simulate human behavior by training on data from the training set. …"
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    RNN performance comparison with/out optimization. حسب Muhammad Usman Tariq (11022141)

    منشور في 2024
    "…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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    Datasets used for the study and their sources. حسب Peter N-jonaam Mahama (15347793)

    منشور في 2023
    "…Projecting into 2030, this study aimed at providing geographical information data for guiding future policies on siting required healthcare facilities. …"
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    Proposed method approach. حسب Muhammad Usman Tariq (11022141)

    منشور في 2024
    "…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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    LSTM model performance. حسب Muhammad Usman Tariq (11022141)

    منشور في 2024
    "…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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    Descriptive statistics. حسب Muhammad Usman Tariq (11022141)

    منشور في 2024
    "…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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    CNN-LSTM Model performance. حسب Muhammad Usman Tariq (11022141)

    منشور في 2024
    "…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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    MLP Model performance. حسب Muhammad Usman Tariq (11022141)

    منشور في 2024
    "…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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    RNN Model performance. حسب Muhammad Usman Tariq (11022141)

    منشور في 2024
    "…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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    CNN Model performance. حسب Muhammad Usman Tariq (11022141)

    منشور في 2024
    "…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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    Bi-directional LSTM Model performance. حسب Muhammad Usman Tariq (11022141)

    منشور في 2024
    "…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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    Image 2_Integrative prognostic modeling for stage III lung adenosquamous carcinoma post-tumor resection: machine learning insights and web-based implementation.png حسب Min Liang (363007)

    منشور في 2024
    "…Introduction<p>The prognostic landscape of stage III Lung Adenosquamous Carcinoma (ASC) following primary tumor resection remains underexplored. A thoughtfully developed prognostic model has the potential to guide clinicians in patient counseling and the formulation of effective therapeutic strategies.…"
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    Image 1_Integrative prognostic modeling for stage III lung adenosquamous carcinoma post-tumor resection: machine learning insights and web-based implementation.png حسب Min Liang (363007)

    منشور في 2024
    "…Introduction<p>The prognostic landscape of stage III Lung Adenosquamous Carcinoma (ASC) following primary tumor resection remains underexplored. A thoughtfully developed prognostic model has the potential to guide clinicians in patient counseling and the formulation of effective therapeutic strategies.…"
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    Supplementary file 1_A study on a real-world data-based VTE risk prediction model for lymphoma patients.docx حسب Changli He (22424818)

    منشور في 2025
    "…</p>Results<p>Combining different imputation, sampling, and feature selection strategies yielded 27 datasets, which were trained across nine algorithms to generate 243 models. The optimal model—Simp-SMOTE_rf_GBM, constructed using random forest imputation, SMOTE oversampling, and gradient boosting machine—achieved the highest predictive performance (AUC = 0.954). …"