Introducing artificial intelligence to the radiation early warning system
Author:
Funder
Conseil National de la Recherche Scientifique
Publisher
Springer Science and Business Media LLC
Subject
Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s11356-021-16771-5.pdf
Reference35 articles.
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2. Arathi M, Govardhan A (2014) Accurate time series classification using shapelets. International Journal of Data Mining & Knowledge Management Process 4:39–47. https://doi.org/10.5121/ijdkp.2014.4204
3. Barde P, Barde P (2012) What to use to express the variability of data: standard deviation or standard error of mean? Perspectives in Clinical Research 3:113–116. https://doi.org/10.4103/2229-3485.100662
4. Biegalski S, Shipman G, Mason L, Pickering M, Altman S (2001) Caribbean radiation early warning system (CREWS). Journal of Radioanalytical and Nuclear Chemistry 248:637–642. https://doi.org/10.1023/A%3A1010624224587
5. Casanovas R, Morant J, López M, Hernández-Girón I, Batalla E, Salvadó M (2011) Performance of data acceptance criteria over 50 months from an automatic real-time environmental radiation surveillance network. Journal of Environmental Radioactivity 102(8):742–748. https://doi.org/10.1016/j.jenvrad.2011.04.001
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