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data algorithm » data algorithms (Expand Search), update algorithm (Expand Search), atlas algorithm (Expand Search)
code algorithm » cosine algorithm (Expand Search), novel algorithm (Expand Search), modbo algorithm (Expand Search)
element data » settlement data (Expand Search), relevant data (Expand Search), movement data (Expand Search)
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data code » data model (Expand Search), data came (Expand Search)
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TreeMap 2016 Stand Size Code Algorithm (Image Service)
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.
Published 2024“…The algorithm was developed and coded in Verilog and simulated using Modelsim. …”
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Pseudocode for the missForestPredict algorithm.
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
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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data and code
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.
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. …”