Abstract
AbstractWe use regression/model trees to build predictive models for radon concentration in soil gas on the basis of environmental data, i.e., barometric pressure, soil temperature, air temperature and rainfall. We build model trees (one per station) for three stations in the Krško basin, Slovenia. The trees predict radon concentration with a (cross-validated) correlation of 0.8, provided radon is influenced only by environmental parameters (and not seismic activity). In periods with seismic activity, however, this correlation is much lower. The increase in prediction error appears a week before earthquakes with local magnitude 0.8 to 3.3.KeywordsRoot Mean Square ErrorSeismic ActivityRegression TreeRadon ConcentrationThermal WaterThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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