Articles | Volume 18, issue 17
https://doi.org/10.5194/gmd-18-5513-2025
https://doi.org/10.5194/gmd-18-5513-2025
Development and technical paper
 | 
02 Sep 2025
Development and technical paper |  | 02 Sep 2025

Accurate and fast prediction of radioactive pollution by kriging coupled with auto-associative models

Raphaël Périllat, Sylvain Girard, and Irène Korsakissok

Data sets

Data for the paper "Accurate and fast prediction of radioactive pollution by Kriging coupled with Auto-Associative Models" Raphaël Périllat https://doi.org/10.5281/zenodo.14747261

Model code and software

perillat/emulation_aam: Metamodeling Scripts for Kriging and Auto-Associative Models Raphaël Périllat https://doi.org/10.5281/zenodo.14856799

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Short summary
We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
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