1 Ocak 2013 Dergi makalesi Açık Erişim

Evrendilek, Fatih; Denizli, Haluk; Yetis, Hakan; Karakaya, Nusret

Dublin Core

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  <dc:creator>Evrendilek, Fatih</dc:creator>
  <dc:creator>Denizli, Haluk</dc:creator>
  <dc:creator>Yetis, Hakan</dc:creator>
  <dc:creator>Karakaya, Nusret</dc:creator>
  <dc:date>2013-01-01</dc:date>
  <dc:description>Concentrations of outdoor radon-222 (Rn-222) in temperate grazed peatland and deciduous forest in northwestern Turkey were measured, compared, and modeled using artificial neural networks (ANNs) and multiple nonlinear regression (MNLR) models. The best-performing multilayer perceptron model selected out of 28 ANNs considerably enhanced accuracy metrics in emulating Rn-222 concentrations relative to the MNLR model. The two ecosystems had similar diel patterns with the lowest Rn-222 concentrations in the afternoon and the highest ones near dawn. Mean level (5.1 + 2.5 Bq m(-3) h(-1)) of Rn-222 in the forest was three times smaller than that (15.8 + 9.7 Bq m(-3)) of Rn-222 in the peatland. Mean Rn-222 level had negative and positive relationships with air temperature and relative humidity, respectively.</dc:description>
  <dc:identifier>https://aperta.ulakbim.gov.trrecord/17117</dc:identifier>
  <dc:identifier>oai:zenodo.org:17117</dc:identifier>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>http://www.opendefinition.org/licenses/cc-by</dc:rights>
  <dc:source>ENVIRONMENTAL MONITORING AND ASSESSMENT 185(7) 5577-5583</dc:source>
  <dc:title>Monitoring spatiotemporal variations of diel radon concentrations in peatland and forest ecosystems based on neural network and regression models</dc:title>
  <dc:type>info:eu-repo/semantics/article</dc:type>
  <dc:type>publication-article</dc:type>
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