Showing 1 - 20 results of 2,805 for search '(( element data algorithm ) OR ((( data code algorithm ) OR ( based forest algorithm ))))', query time: 0.46s Refine Results
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    TreeMap 2016 Stand Size Code Algorithm (Image Service) by U.S. Forest Service (17476914)

    Published 2024
    “…format=iso19139 "> ISO-19139 metadata</a></li><li> <a href="https://data-usfs.hub.arcgis.com/datasets/usfs::treemap-2016-stand-size-code-algorithm-image-service "> ArcGIS Hub Dataset</a></li><li> <a href="https://apps.fs.usda.gov/fsgisx01/rest/services/RDW_ForestEcology/TreeMap_2016_StandSizeCode_Algorithm/ImageServer "> ArcGIS GeoService</a></li></ul><div> For complete information, please visit <a href="https://data.gov">https://data.gov</a>.…”
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    G R code algorithm. by R. Sakthivel (2589547)

    Published 2024
    “…The algorithm was developed and coded in Verilog and simulated using Modelsim. …”
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    Pseudocode for the missForestPredict algorithm. by Elena Albu (15181070)

    Published 2025
    “…The missForestPredict R package proposes an adaptation of the missForest imputation algorithm that is fast, user-friendly and tailored for prediction settings. …”
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    Dual deconvolution algorithm: analysis code with experimental data by Wonshik Choi (18877660)

    Published 2025
    “…<p dir="ltr">This software package provides key algorithms for dual-deconvolution microscopy analysis, along with both experimental and numerical data. …”
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    Code. by Shamsuz Zoha (22339469)

    Published 2025
    Subjects:
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    data and code by PENGCHENG LIU (20680641)

    Published 2025
    “…Combined with the road network data, this algorithm regards the trajectory data as a signal that changes dynamically with time, converts it from time domain to frequency domain through Fourier transform, fits the trajectory points in the spectrum domain, and converts the discrete trajectory points into time continuous line elements.…”
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    Improved random forest algorithm. by Zhen Zhao (159931)

    Published 2025
    “…Compared with MDA-RF, the prediction accuracy of the improved RF built on the same subset increased by 1.7%, indicating that improving the bootstrap sampling of random forest by using the K-means++ clustering algorithm can enhance model accuracy to some extent. …”