title: Bagged neural network model for prediction of the mean indoor radon concentration in the municipalities in Czech Republic.
abstract: The purpose of the study is to determine radon-prone areas in the Czech Republic based on the measurements of indoor radon concentration and independent predictors (rock type and permeability of the bedrock, gamma dose rate, GPS coordinates and the average age of family houses). The relationship between the mean observed indoor radon concentrations in monitored areas (∼22% municipalities) and the independent predictors was modelled using a bagged neural network. Levels of mean indoor radon concentration in the unmonitored areas were predicted using the bagged neural network model fitted for the monitored areas. The propensity to increased indoor radon was determined by estimated probability of exceeding the action level of 300Bq/m3.
authors.affiliation: National Radiation Protection Institute, Bartoskova 28, 140 00, Praha 4, Czech Republic. Electronic address: jana.timkova@suro.cz.
authors.forename: Jana
authors.initials: J
authors.lastname: Timkova
authors.affiliation: National Radiation Protection Institute, Bartoskova 28, 140 00, Praha 4, Czech Republic. Electronic address: ivana.fojtikova@suro.cz.
authors.forename: Ivana
authors.initials: I
authors.lastname: Fojtikova
authors.affiliation: Czech Geological Survey, Geologicka 6, 152 00, Praha 5, Czech Republic. Electronic address: petra.pacherova@geology.cz.
authors.forename: Petra
authors.initials: P
authors.lastname: Pacherova
mesh_terms: D000396:Air Pollutants, Radioactive / Q000032:analysis*; D016902:Air Pollution, Indoor / Q000706:statistics & numerical data*; D000398:Air Pollution, Radioactive / Q000706:statistics & numerical data*; D018153:Czech Republic; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D011834:Radiation Monitoring; D011886:Radon / Q000032:analysis
chemical_list: D000396:Air Pollutants, Radioactive; D011886:Radon
keywords: Bagged neural network; Czech Republic; Gamma dose rate; Indoor radon; Lithology; Predictive mapping