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MUSE-RASA captures human dimension in climate-energy-economic models via global geoAI-ML agent datasets
This article provides a combined geospatial artificial intelligence-machine learning, geoAI-ML, agent-based, data-driven, technology-rich, bottom-up approach and datasets for capturing the human dimension in climate-energy-economy models. Seven stages were required to conduct this study and build th...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10570386/ https://www.ncbi.nlm.nih.gov/pubmed/37828067 http://dx.doi.org/10.1038/s41597-023-02529-w |