title: Layered neural networks based analysis of radon concentration and environmental parameters in earthquake prediction.
abstract: A layered neural network (LNN) has been employed to estimate the radon concentration in soil related to the environmental parameters. This technique can find any functional relationship between the radon concentration and the environmental parameters. Analysis of the data obtained from a site in Thailand indicates that this approach is able to differentiate time variation of radon concentration caused by environmental parameters from those arising by anomaly phenomena in the earth (e.g. earthquake). This method is compared with a linear computational technique based on impulse responses from multivariable time series. It is indicated that the proposed method can give a better estimation of radon variations related to environmental parameters that may have a non-linear effect on the radon concentration in soil, such as rainfall.
authors.affiliation: Faculty of Physics and Nuclear Sciences, Amir Kabir University of Technology, Tehran, Iran. anegar@seai.neda.net.ir
authors.forename: A
authors.initials: A
authors.lastname: Negarestani
authors.forename: S
authors.initials: S
authors.lastname: Setayeshi
authors.forename: M
authors.initials: M
authors.lastname: Ghannadi-Maragheh
authors.forename: B
authors.initials: B
authors.lastname: Akashe
mesh_terms: D004189:Disaster Planning; D004190:Disasters; D005544:Forecasting; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D011886:Radon / Q000032:analysis*
chemical_list: D011886:Radon