Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/14059
Authors: Ambrosino, Fabio* 
Sabbarese, Carlo* 
Roca, V.* 
Giudicepietro, Flora* 
Chiodini, Giovanni* 
Title: Analysis of 7-years Radon time series at Campi Flegrei area (Naples, Italy) using artificial neural network method
Journal: Applied Radiation and Isotopes 
Series/Report no.: /163 (2020)
Publisher: Elsevier
Issue Date: Sep-2020
DOI: 10.1016/j.apradiso.2020.109239
Keywords: Anomaly detection; Artificial neural network; Influencing parameter; Radon; Signal forecasting; Signal replication
Abstract: 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.
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