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Evrendilek, Fatih; Denizli, Haluk; Yetis, Hakan; Karakaya, Nusret
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/17117</identifier> <creators> <creator> <creatorName>Evrendilek, Fatih</creatorName> <givenName>Fatih</givenName> <familyName>Evrendilek</familyName> <affiliation>Abant Izzet Baysal Univ, Dept Environm Engn, Bolu, Turkey</affiliation> </creator> <creator> <creatorName>Denizli, Haluk</creatorName> <givenName>Haluk</givenName> <familyName>Denizli</familyName> <affiliation>Abant Izzet Baysal Univ, Dept Phys, Bolu, Turkey</affiliation> </creator> <creator> <creatorName>Yetis, Hakan</creatorName> <givenName>Hakan</givenName> <familyName>Yetis</familyName> <affiliation>Abant Izzet Baysal Univ, Dept Phys, Bolu, Turkey</affiliation> </creator> <creator> <creatorName>Karakaya, Nusret</creatorName> <givenName>Nusret</givenName> <familyName>Karakaya</familyName> <affiliation>Abant Izzet Baysal Univ, Dept Environm Engn, Bolu, Turkey</affiliation> </creator> </creators> <titles> <title>Monitoring Spatiotemporal Variations Of Diel Radon Concentrations In Peatland And Forest Ecosystems Based On Neural Network And Regression Models</title> </titles> <publisher>Aperta</publisher> <publicationYear>2013</publicationYear> <dates> <date dateType="Issued">2013-01-01</date> </dates> <resourceType resourceTypeGeneral="Text">Journal article</resourceType> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/17117</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1007/s10661-012-2968-3</relatedIdentifier> </relatedIdentifiers> <rightsList> <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights> <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights> </rightsList> <descriptions> <description descriptionType="Abstract">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.</description> </descriptions> </resource>
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