Showing 1 - 20 results of 25 for search '(( primary data production optimization algorithm ) OR ( binary b codon optimization algorithm ))', query time: 0.48s Refine Results
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    The robustness test results of the model. by Xini Fang (20861990)

    Published 2025
    “…Finally, an improved RF model is constructed by optimizing the parameters of the RF algorithm. The data selected is mainly from RESSET/DB, covering the issuance, trading, and rating data of fixed-income products such as bonds, government bonds, and corporate bonds, and provides basic information, net value, position, and performance data of funds. …”
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    Construction process of RF. by Xini Fang (20861990)

    Published 2025
    “…Finally, an improved RF model is constructed by optimizing the parameters of the RF algorithm. The data selected is mainly from RESSET/DB, covering the issuance, trading, and rating data of fixed-income products such as bonds, government bonds, and corporate bonds, and provides basic information, net value, position, and performance data of funds. …”
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    Data used to drive the Double Layer Carbon Model in the Qinling Mountains. by Huiwen Li (17705280)

    Published 2024
    “…It relies on comprehensive input data, including initial SOC stocks, climate data, and vegetation production to drive these simulations.…”
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    Supporting data for “The role of forest composition heterogeneity on temperate ecosystem carbon dynamic under climate change" by Ziyu Lin (9151064)

    Published 2025
    “…The process includes (1) harmonizing Landsat 5, 7, 8, and Sentinel-2 data using the HLS algorithm, and (2) filling temporal gaps with an optimized object-based STARFM fusion algorithm. …”
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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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    Supplementary file 1_Development of a venous thromboembolism risk prediction model for patients with primary membranous nephropathy based on machine learning.docx by Lian Li (49049)

    Published 2025
    “…Objective<p>This study utilizes real-world data from primary membranous nephropathy (PMN) patients to preliminarily develop a venous thromboembolism (VTE) risk prediction model with machine learning. …”