Showing 1 - 20 results of 36 for search '(( primary data required optimization algorithm ) OR ( pine tree wolf optimization algorithm ))', query time: 1.08s Refine Results
  1. 1

    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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    ECE6379_PSOM.zip by Xingpeng Li (11825663)

    Published 2021
    “…Optimization algorithms that are commonly used to solve these problems will also be covered including linear programming, mixed-integer linear programming, Lagrange relaxation, dynamic programming, branch and bound, and duality theory.…”
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    Datasets used for the study and their sources. by Peter N-jonaam Mahama (15347793)

    Published 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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    Predicting the Shear Viscosity of Carbonated Aqueous Amine Solutions and Their Blends by Using an Artificial Neural Network Model by Ali Aminian (9580734)

    Published 2020
    “…A total of 1682 amine + CO<sub>2</sub> + water viscosity data sets for primary, secondary, and tertiary amines and 220 data points for further accuracy examinations were used. …”
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    Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics by Zhichao Liu (191718)

    Published 2019
    “…However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …”
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    Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics by Zhichao Liu (191718)

    Published 2019
    “…However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …”
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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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