Long Short Term Memory networks (LSTM)-Monte-Carlo simulation of soil ionization using radon

dc.contributor.authorMuhammad, Ahmad
dc.contributor.authorKulahci, Fatih
dc.contributor.authorSalh, Hemn
dc.contributor.authorRashid, Pishtiwan Akram Hama
dc.date.accessioned2026-08-12T17:36:04Z
dc.date.issued2021
dc.departmentFırat Üniversitesi
dc.description.abstractEarthquake events are usually associated with atmospheric processes variations. Some of the important events in seismic periods include the atmospheric electricity/conductivity modification, which mostly depends on the ion population in the vicinity of earthquake preparation area. Radon, together with cosmic radiation are the major ionization sources in the lower troposphere. The radon induced soil ion-pair production rate was estimated for Erzincan, a city along the North Anatolian Fault Zone, Turkey. The Long Short-Term Memory networks (LSTM's) and Monte Carlo method are proposed to account for uncertainty in estimating the ion production rate. The advantage of the LSTM model is taken to study radon anomalies during the M = 5 Girlevik earthquake, Erzincan. Radon concentration is found to increase prior to the 5.0 Girlevik earthquake. According to estimations, 23 x 109 ion-pairs m- 3s-1 were generated at 1 m depth from the Earth's surface during this earthquake. The soil-ion production estimation rate due to radon and its progeny in Erzincan is at the order of 109 ion-pairs m- 3s- 1. When these generated ions and charged aerosols reach the surface and were added to other ionization sources, parameters such as the near surface conductivity and electric field would be modified. In addition, under pronounced conditions could favor ionospheric perturbations.
dc.identifier.doi10.1016/j.jastp.2021.105688
dc.identifier.issn1364-6826
dc.identifier.issn1879-1824
dc.identifier.orcid0000-0002-2367-2980
dc.identifier.orcid0000-0001-6566-4308
dc.identifier.orcid0000-0002-5067-8982
dc.identifier.orcid0000-0003-3886-7956
dc.identifier.scopus2-s2.0-85107089731
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1016/j.jastp.2021.105688
dc.identifier.urihttps://hdl.handle.net/11508/57785
dc.identifier.volume221
dc.identifier.wosWOS:000672855100004
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherPergamon-Elsevier Science Ltd
dc.relation.ispartofJournal of Atmospheric and Solar-Terrestrial Physics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260511
dc.subjectRadon
dc.subjectNear surface ionization
dc.subjectMonte Carlo simulation
dc.subjectEarthquake forecasting
dc.subjectDeep learning
dc.subjectSeismo-ionospheric coupling
dc.subjectLSTM
dc.titleLong Short Term Memory networks (LSTM)-Monte-Carlo simulation of soil ionization using radon
dc.typeArticle

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