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Showing 1 - 20 results of 23 for search '(( primary data bayesian optimization algorithm ) OR ( binary image swarm optimization algorithm ))', query time: 0.48s Refine Results
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    Models’ performance without optimization. by Muhammad Usman Tariq (11022141)

    Published 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 performance comparison with/out optimization. by Muhammad Usman Tariq (11022141)

    Published 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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    XNet: A Bayesian Approach to Extracted Ion Chromatogram Clustering for Precursor Mass Spectrometry Data by Mathew Gutierrez (5844431)

    Published 2019
    “…While tandem mass spectrometry remains a primary method for identification and quantification, species-resolved precursor data provides a rich source of unexploited information. …”
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    Proposed method approach. by Muhammad Usman Tariq (11022141)

    Published 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. by Muhammad Usman Tariq (11022141)

    Published 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. by Muhammad Usman Tariq (11022141)

    Published 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. by Muhammad Usman Tariq (11022141)

    Published 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. by Muhammad Usman Tariq (11022141)

    Published 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. by Muhammad Usman Tariq (11022141)

    Published 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. by Muhammad Usman Tariq (11022141)

    Published 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. by Muhammad Usman Tariq (11022141)

    Published 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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    Thesis-RAMIS-Figs_Slides by Felipe Santibañez-Leal (10967991)

    Published 2024
    “…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”
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