Showing 1 - 20 results of 25 for search '(( elements mges algorithm ) OR ((( settlement data algorithm ) OR ( neural codingn_ algorithm ))))', query time: 0.25s Refine Results
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    The schematic diagram of the hierarchical clustering algorithm. by Xiaojie Feng (6873953)

    Published 2025
    Subjects: “…original multidimensional data…”
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    The silhouette coefficient scores for different algorithms at various levels. by Xiaojie Feng (6873953)

    Published 2025
    Subjects: “…original multidimensional data…”
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    Data types and sources. by Xiaojie Feng (6873953)

    Published 2025
    Subjects: “…original multidimensional data…”
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    Spatial distribution level results. by Xiaojie Feng (6873953)

    Published 2025
    Subjects: “…original multidimensional data…”
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    Classification of accessibility levels. by Xiaojie Feng (6873953)

    Published 2025
    Subjects: “…original multidimensional data…”
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    S1 File - by Xiaojie Feng (6873953)

    Published 2025
    Subjects: “…original multidimensional data…”
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    Data Sheet 1_Decoding the association between health level and human settlements environment: a machine learning-driven provincial analysis in China.zip by Haidong Zhu (103585)

    Published 2025
    “…Background<p>Rapid urbanization in China has significantly reshaped the human settlement environment (HSE), bringing opportunities and challenges for public health. …”
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    LandScan Global, 30 Arc-second Annual Global Gridded Population Datasets from 2000 to 2022 by Viswadeep Lebakula (16069243)

    Published 2025
    “…Using an innovative approach that combines geospatial science, remote sensing technology, and machine learning algorithms, LandScan Global is a global population distribution data, at 30 arc seconds (roughly 1km at equator), representing an ambient (24 hour average) population. …”
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    A Machine-Insight-Based Geocomputational Approach to Decode the Complexities of the Restless Landscapes: Toward Integration of Imaginations and Planning Interventions by Nilanjan Bal (21727652)

    Published 2025
    “…The learning cloud incorporates settlement-wise data in an encoded format to run the XGBoost machine learning algorithm. …”
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    Data Sheet 2_Characterization of the salivary microbiome in healthy individuals under fatigue status.docx by Xianhui Peng (14551488)

    Published 2025
    “…Phenotypic predictions indicated a significant increase in the proportion of bacteria harboring Mobile Genetic Elements (MGEs) (p=0.048), alongside significant reductions in the proportion of aerobic bacteria (p=0.006) and biofilm-forming capacity (p=0.002) in the FTG group. …”
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    Table 3_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

    Published 2025
    “…Phenotypic predictions indicated a significant increase in the proportion of bacteria harboring Mobile Genetic Elements (MGEs) (p=0.048), alongside significant reductions in the proportion of aerobic bacteria (p=0.006) and biofilm-forming capacity (p=0.002) in the FTG group. …”