يعرض 1 - 19 نتائج من 19 نتيجة بحث عن '(( binary water process optimization algorithm ) OR ( primary data dose optimization algorithm ))', وقت الاستعلام: 0.61s تنقيح النتائج
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    Hyperparameters of the LSTM Model. حسب Ahmed M. Elshewey (21463867)

    منشور في 2025
    "…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"
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    The AD-PSO-Guided WOA LSTM framework. حسب Ahmed M. Elshewey (21463867)

    منشور في 2025
    "…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"
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    Prediction results of individual models. حسب Ahmed M. Elshewey (21463867)

    منشور في 2025
    "…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"
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    Classification performance after optimization. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
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    ANOVA test for optimization results. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
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    Wilcoxon test results for optimization. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
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    Wilcoxon test results for feature selection. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
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    Feature selection metrics and their definitions. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
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    Statistical summary of all models. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
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    Feature selection results. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
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    ANOVA test for feature selection. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
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    Classification performance of ML and DL models. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
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    DataSheet_2_Optimising Treatment Outcomes for Children and Adults Through Rapid Genome Sequencing of Sepsis Pathogens. A Study Protocol for a Prospective, Multi-Centre Trial (DIREC... حسب Adam D. Irwin (11011752)

    منشور في 2021
    "…We set out to demonstrate the feasibility and diagnostic accuracy of pathogen sequencing direct from clinical samples, and estimate the impact of this approach on time to effective therapy when integrated with personalised software-guided antimicrobial dosing in children and adults on ICU with sepsis.</p>Methods<p>The DIRECT study is a pilot prospective, non-randomized multicentre trial of an integrated diagnostic and therapeutic algorithm combining rapid direct pathogen sequencing and software-guided, personalised antibiotic dosing in children and adults with sepsis on ICU.…"
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    DataSheet_1_Optimising Treatment Outcomes for Children and Adults Through Rapid Genome Sequencing of Sepsis Pathogens. A Study Protocol for a Prospective, Multi-Centre Trial (DIREC... حسب Adam D. Irwin (11011752)

    منشور في 2021
    "…We set out to demonstrate the feasibility and diagnostic accuracy of pathogen sequencing direct from clinical samples, and estimate the impact of this approach on time to effective therapy when integrated with personalised software-guided antimicrobial dosing in children and adults on ICU with sepsis.</p>Methods<p>The DIRECT study is a pilot prospective, non-randomized multicentre trial of an integrated diagnostic and therapeutic algorithm combining rapid direct pathogen sequencing and software-guided, personalised antibiotic dosing in children and adults with sepsis on ICU.…"
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    Supplementary Material for: The Therapeutic Evaluation of Steroids in IgA Nephropathy Global (TESTING) Study: Trial Design and Baseline Characteristics حسب Wong M.G. (11640685)

    منشور في 2021
    "…By the time the excess of serious infections was observed, 262 participants had been randomized to the original full-dose treatment algorithm, and an interim analysis was reported in 2016. …"
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    Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles حسب Soham Savarkar (21811825)

    منشور في 2025
    "…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…"