Ambrosino F, Sabbarese C, Roca V, Giudicepietro F, Chiodini G
Centre for Isotopic Research on Cultural and Environmental Heritage (CIRCE), Department of Mathematics and Physics, University of Campania "Luigi Vanvitelli", Viale Lincoln 5, 81100, Caserta, Italy; National Institute of Nuclear Physics, Branch of Naples, Via Cinthia 21, 80126, Naples, Italy.
Centre for Isotopic Research on Cultural and Environmental Heritage (CIRCE), Department of Mathematics and Physics, University of Campania "Luigi Vanvitelli", Viale Lincoln 5, 81100, Caserta, Italy; National Institute of Nuclear Physics, Branch of Naples, Via Cinthia 21, 80126, Naples, Italy.
Appl Radiat Isot. 2020 Sep;163:109239. doi: 10.1016/j.apradiso.2020.109239. Epub 2020 May 24.
This paper reports the analysis of soil Rn 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.
本文报道了对意大利那不勒斯弗莱格雷火山口7年期间记录的土壤氡数据的分析。通过人工神经网络（ANN）方法估算了氡活度浓度与影响气体排放的几个地球物理、地球化学和气象参数之间的关系。分析目标是：根据影响参数估算（复制）氡时间序列、预测其未知部分以及寻找异常。结果证明：（i）人工神经网络方法的有效性；（ii）通过与使用不同方法的先前研究进行比较表明，氡随火山口的活动期而变化。
