Zmazek B, Todorovski L, Dzeroski S, Vaupotic J, Kobal I
J. Stefan Institute, Ljubljana 1000, Slovenia.
Appl Radiat Isot. 2003 Jun;58(6):697-706. doi: 10.1016/s0969-8043(03)00094-0.
Different regression methods have been used to predict radon concentration in soil gas on the basis of environmental data, i.e. barometric pressure, soil temperature, air temperature and rainfall. Analyses of the radon data from three stations in the Krsko basin, Slovenia, have shown that model trees outperform other regression methods. A model has been built which predicts radon concentration with a correlation of 0.8, provided it is influenced only by the environmental parameters. In periods with seismic activity this correlation is much lower. This decrease in predictive accuracy appears 1-7 days before earthquakes with local magnitude 0.8-3.3.
已使用不同的回归方法，根据环境数据（即气压、土壤温度、气温和降雨量）预测土壤气体中的氡浓度。对斯洛文尼亚克尔什科盆地三个站点的氡数据进行分析后发现，模型树的表现优于其他回归方法。已构建了一个模型，该模型在仅受环境参数影响的情况下，预测氡浓度的相关性为0.8。在地震活动期间，这种相关性要低得多。这种预测准确性的下降出现在震级为0.8 - 3.3的地震前1 - 7天。
