MUSE-RASA captures human dimension in climate-energy-economic models via global geoAI-ML agent datasets

MUSE-RASA captures human dimension in climate-energy-economic models via global geoAI-ML agent datasets

Abstract 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...

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Bibliographic Details
Main Authors: Diego Moya, Dennis Copara, Alexis Olivo, Christian Castro, Sara Giarola, Adam Hawkes
Format: Article
Language:English
Published: Nature Portfolio 2023-10-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-023-02529-w

Internet

https://doi.org/10.1038/s41597-023-02529-w

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