Showing 1 - 20 results of 22 for search '(( binary mainly driven optimization algorithm ) OR ( primary data step optimization algorithm ))', query time: 0.53s Refine Results
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    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

    Published 2025
    “…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”
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    Dendrogram of the stock prices. by Muhammad Hilal Alkhudaydi (21560690)

    Published 2025
    “…This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …”
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    Descriptive statistics on stock prices. by Muhammad Hilal Alkhudaydi (21560690)

    Published 2025
    “…This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …”
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    Correlation heatmap of the principal components. by Muhammad Hilal Alkhudaydi (21560690)

    Published 2025
    “…This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …”
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    SBM 2023 Poster: Development and Validation of Multivariable Prediction Algorithms to Estimate Future Walking Behavior in Adults: Retrospective Cohort Study by Junghwan Park (15195436)

    Published 2023
    “…</p> <p><strong>Objectives: </strong>To develop and validate algorithms that predict walking (i.e., >5 minutes) within the next 3 hours, predicted from the participants’ previous five weeks’ steps per minute data.…”
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    Table_1_One-Time Optimization of Advanced T Cell Culture Media Using a Machine Learning Pipeline.DOCX by Paul Grzesik (11136582)

    Published 2021
    “…Here we present the implementation of a machine learning pipeline into the DoE-based design of cell culture media to optimize T cell cultures in one experimental step (one-time optimization). …”
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    Early Parkinson’s disease identification via hybrid feature selection from multi-feature subsets and optimized CatBoost with SMOTE by Subhashree Mohapatra (17387852)

    Published 2025
    “…The proposed framework leverages a strong categorical boosting (CatBoost) algorithm optimized using Grid Search Optimization (GSO). …”
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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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    Table_4_High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis.XLSX by Hui Tang (226667)

    Published 2019
    “…<p>Quantifying or labeling the sample type with high quality is a challenging task, which is a key step for understanding complex diseases. Reducing noise pollution to data and ensuring the extracted intrinsic patterns in concordance with the primary data structure are important in sample clustering and classification. …”
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    Table_2_High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis.XLSX by Hui Tang (226667)

    Published 2019
    “…<p>Quantifying or labeling the sample type with high quality is a challenging task, which is a key step for understanding complex diseases. Reducing noise pollution to data and ensuring the extracted intrinsic patterns in concordance with the primary data structure are important in sample clustering and classification. …”
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    Table_1_High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis.docx by Hui Tang (226667)

    Published 2019
    “…<p>Quantifying or labeling the sample type with high quality is a challenging task, which is a key step for understanding complex diseases. Reducing noise pollution to data and ensuring the extracted intrinsic patterns in concordance with the primary data structure are important in sample clustering and classification. …”
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    Table_3_High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis.XLS by Hui Tang (226667)

    Published 2019
    “…<p>Quantifying or labeling the sample type with high quality is a challenging task, which is a key step for understanding complex diseases. Reducing noise pollution to data and ensuring the extracted intrinsic patterns in concordance with the primary data structure are important in sample clustering and classification. …”