Machine learning techniques for the prediction of indoor gamma-ray dose rates - strengths, weaknesses and implications for epidemiology
We investigate methods that improve the estimation of indoor gamma ray dose rates at locations where measurements had not been made. These new predictions use a greater range of modelling techniques and larger variety of explanatory variables than our previous examinations of this subject. Specifica...
| Päätekijät: | , , , , |
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| Aineistotyyppi: | Journal article |
| Kieli: | English |
| Julkaistu: |
Elsevier
2024
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