research data . Dataset . 2021

Sample data for "Machine learning for large-scale forecasting"

Dilli Paudel; Hendrik Boogaard; Allard de Wit; Sander Janssen; Sjoukje Osinga; Christos Pylianidis; Ioannis Athanasiadis;
Open Access
  • Published: 01 Jan 2021
  • Publisher: Zenodo
Abstract
<p>This dataset includes sample data for the Netherlands to run the machine learning baseline as described in the paper titled <em>Machine learning for large-scale crop yield forecasting</em>, accessible at&nbsp;<a href="https://doi.org/10.1016/j.agsy.2020.103016">https://doi.org/10.1016/j.agsy.2020.103016</a>.&nbsp;The software implementation of the machine learning baseline is available at:&nbsp;<a href="https://github.com/BigDataWUR/MLforCropYieldForecasting">https://github.com/BigDataWUR/MLforCropYieldForecasting</a>.</p> <p><strong>Notes:</strong></p> <p>The NUTS classification (Nomenclature of territorial units for statistics) is a hierarchical system for ...
Persistent Identifiers
Subjects
free text keywords: Crop yield prediction; Machine learning; Modularity; Reusability; Large-scale crop yield forecasting., crop yield prediction, machine learning, modularity, reusability, large-scale crop yield forecasting
Funded by
EC| CYBELE
Project
CYBELE
FOSTERING PRECISION AGRICULTURE AND LIVESTOCK FARMING THROUGH SECURE ACCESS TO LARGE-SCALE HPC-ENABLED VIRTUAL INDUSTRIAL EXPERIMENTATION ENVIRONMENT EMPOWERING SCALABLE BIG DATA ANALYTICS
  • Funder: European Commission (EC)
  • Project Code: 825355
  • Funding stream: H2020 | IA
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Dataset . 2021
Provider: Zenodo
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Dataset . 2021
Provider: NARCIS
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