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2,369 datasets for “optimization”

  1. data.overheid.nl

    Business survey Netherlands; to sector/branches

    CBS OpenDataUpdated 9 Nov 2026

    … As a result it is possible to detect turning points in optimism or pessimism at an early stage …

    • JSON
    • ATOM
  2. data.gov.uk

    UKCCSRC Call 2 Project: Investigating the radiative heat flux in small and large scale oxy-coal furnaces for CFD model development and system scale up

    British Geological Survey (BGS)Updated 13 Nov 2026

    … The developed and validated CFD models may then be employed with more confidence to predict, analyse and optimise …

  3. data.gov.au

    Soil and Landscape Grid National Soil Attribute Maps - Available Volumetric Water Capacity (Percent) (3 arc second resolution) Version 2

    Terrestrial Ecosystem Research Network's Data DiscoveryUpdated 10 Jun 2026

    … Cloud Optimised GeoTIFF

    • HTML
    • PDF
    • WMS
    • WCS
    • PNG
  4. GovData Germany

    Kindertageseinrichtungen Wuppertal

    Open.NRWUpdated 12 Nov 2026

    … Zur Optimierung der Georeferenzierung und Ergänzung um präsentationsrelevante Attribute wird ein Auszug aus diesen Daten wöchentlich automatisiert in …

    • ZIP
    • KML
    • APPLICATION/GML+XML
    • JSON
    • WFS
    • WMS
  5. Data.gov Catalog

    Topo-bathymetric digital elevation models of the upper Merced and Tuolumne Rivers in California derived from hyperspectral image data and near-infrared LiDAR acquired in 2014

    U.S. Geological SurveyUpdated 23 Sept 2021

    … Water depths were estimated from the imagery using the Optimal Band Ratio Analysis (OBRA) depth retrieval algorithm, a …

    • XML
  6. data.gov.au

    WAMSI 2 - Dredging Node 3.2.1 - Plume Characteristics (Field) - Field Trip 2

    Australian Ocean Data NetworkUpdated 23 Jun 2025

    … the dredge-generated plume; (3) Provide data to optimize and validate plume modelling; (5) Assess the spatial and …

    • HTML
    • PNG
  7. data.gov.au

    Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness

    Geoscience Australia DataUpdated 18 Nov 2025

    … 1) of five variable selection methods, one is suitable for selecting optimal RF predictive models; 2) traditional model …

    • HTML
  8. data.gov.au

    Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness

    Geoscience Australia DataUpdated 8 Jan 2026

    … 1) of five variable selection methods, one is suitable for selecting optimal RF predictive models; 2) traditional model …

    • HTML
  9. data.gov.au

    Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness

    Geoscience Australia DataUpdated 20 Jan 2026

    … 1) of five variable selection methods, one is suitable for selecting optimal RF predictive models; 2) traditional model …

    • HTML
  10. data.gov.au

    Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness

    Geoscience Australia DataUpdated 2 Mar 2026

    … 1) of five variable selection methods, one is suitable for selecting optimal RF predictive models; 2) traditional model …

    • HTML
  11. data.gov.au

    Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness

    Geoscience Australia DataUpdated 7 Mar 2026

    … 1) of five variable selection methods, one is suitable for selecting optimal RF predictive models; 2) traditional model …

    • HTML
  12. data.gov.au

    Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness

    Geoscience Australia DataUpdated 25 Mar 2026

    … 1) of five variable selection methods, one is suitable for selecting optimal RF predictive models; 2) traditional model …

    • HTML
  13. data.gov.au

    Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness

    Geoscience Australia DataUpdated 20 Apr 2026

    … 1) of five variable selection methods, one is suitable for selecting optimal RF predictive models; 2) traditional model …

    • HTML
  14. data.gov.au

    Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness

    Geoscience Australia DataUpdated 30 Apr 2026

    … 1) of five variable selection methods, one is suitable for selecting optimal RF predictive models; 2) traditional model …

    • HTML
  15. Data.gov Catalog

    EMIT L2B Estimated Methane Plume Complexes 60 m V001

    LP DAAC;NASA/JPL/EMITUpdated 5 Nov 2026

    … one Cloud Optimized GeoTIFF (COG) file at a spatial resolution of 60 meters (m) and one GeoJSON file …

    • ISO
    • BIN
    • PDF
  16. data.gov.au

    Adavale Basin 2D Reprocessed Seismic Data Package 2023

    Geoscience Australia DataUpdated 16 Oct 2025

    … deconvolution, and constructing an accurate velocity model to optimise pre-stack time and depth migration. Both stacks and …

    • ZIP
  17. data.gov.au

    Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness

    Australian Ocean Data NetworkUpdated 20 Dec 2025

    … 1) of five variable selection methods, one is suitable for selecting optimal RF predictive models; 2) traditional model …

    • HTML
  18. data.gov.au

    Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness

    Australian Ocean Data NetworkUpdated 11 Jan 2026

    … 1) of five variable selection methods, one is suitable for selecting optimal RF predictive models; 2) traditional model …

    • HTML
  19. data.gov.au

    Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness

    Australian Ocean Data NetworkUpdated 23 Jan 2026

    … 1) of five variable selection methods, one is suitable for selecting optimal RF predictive models; 2) traditional model …

    • HTML
  20. data.gov.au

    Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness

    Australian Ocean Data NetworkUpdated 12 Feb 2026

    … 1) of five variable selection methods, one is suitable for selecting optimal RF predictive models; 2) traditional model …

    • HTML
“optimization” datasets · Open Data Finder