This paper reports the analysis of soil ²²²Rn data recorded over 7-years in the volcanic caldera of Campi Flegrei (Naples-Italy). The relationship between Radon activity concentration and several geophysical, geochemical and meteorological parameters, influencing the gas emissions, is estimated by the Artificial Neural Network (ANN) method. The analysis goals are: the estimation (replication) of the Radon time series from influencing parameters, the forecasting of an unknown part of it, and the search for anomalies. Results prove: (i) the effectiveness of the ANN method; (ii) Radon follow the periods of agitation of the caldera, demonstrated by the comparison with previous works using different methods.

本文报告了7年间在Campi Flegrei（意大利那不勒斯）火山口中记录的土壤²²² Rn数据的分析。通过人工神经网络（ANN）方法估算Rad活度浓度与影响气体排放的若干地球物理，地球化学和气象参数之间的关系。分析目标是：根据影响参数对Radon时间序列进行估计（复制），预测其中的未知部分以及查找异常。结果证明：（i）人工神经网络方法的有效性；（ii）follow跟随破火山口的搅动期，通过与使用不同方法的先前作品的比较来证明。