Significance of Rent Attributes in Prediction of Earthquake Damage in Adapazari, Turkey

dc.contributor.author Tayfur, Gökmen
dc.contributor.author Bektaş, Birkan
dc.contributor.author Duvarcı, Yavuz
dc.coverage.doi 10.14311/NNW.2014.24.036
dc.date.accessioned 2017-06-13T06:27:03Z
dc.date.available 2017-06-13T06:27:03Z
dc.date.issued 2014
dc.description.abstract This paper analyses rent-based determinants of earthquake damage from an urban planning perspective with the data gathered from Adapazari, Turkey, after the disaster in 1999 Eastern Marmara Earthquake (EME). The study employs linear regression, log-linear regression, and artificial neural networks (ANN) methods for cross-verification of results and for finding out the significant urban rent attribute(s) responsible for the damage. All models used are equally capable of predicting the earthquake damage and converge to similar results even if the data are limited. Of the rent variables, the physical density is proved to be especially significant in predicting earthquake damage, while the land value contributes to building resistance. Thus, urban rent can be the primary tool for planners to help reduce the fatalities in preventive planning studies. en_US
dc.identifier.citation Tayfur, G., Bektaş, B., and Duvarcı, Y. (2014). Significance of rent attributes in prediction of earthquake damage in Adapazari, Turkey. Neural Network World, 24(6), 637-653. doi:10.14311/NNW.2014.24.036 en_US
dc.identifier.doi 10.14311/NNW.2014.24.036
dc.identifier.doi 10.14311/NNW.2014.24.036 en_US
dc.identifier.issn 2336-4335
dc.identifier.issn 1210-0552
dc.identifier.issn 1210-0552
dc.identifier.scopus 2-s2.0-84920717557
dc.identifier.uri https://doi.org/10.14311/NNW.2014.24.036
dc.identifier.uri https://hdl.handle.net/11147/5745
dc.language.iso en en_US
dc.publisher Czech Technical University in Prague en_US
dc.relation.ispartof Neural Network World en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Artificial neural network en_US
dc.subject Earthquakes en_US
dc.subject Regression analysis en_US
dc.subject Urban development en_US
dc.subject Urban rent en_US
dc.title Significance of Rent Attributes in Prediction of Earthquake Damage in Adapazari, Turkey en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.institutional Tayfur, Gökmen
gdc.author.institutional Duvarcı, Yavuz
gdc.author.yokid 117217
gdc.bip.impulseclass C5
gdc.bip.influenceclass C5
gdc.bip.popularityclass C5
gdc.coar.access open access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department İzmir Institute of Technology. Civil Engineering en_US
gdc.description.endpage 653 en_US
gdc.description.issue 6 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q4
gdc.description.startpage 637 en_US
gdc.description.volume 24 en_US
gdc.description.wosquality Q4
gdc.identifier.openalex W2329784294
gdc.identifier.wos WOS:000348408100005
gdc.index.type WoS
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gdc.oaire.accesstype BRONZE
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gdc.oaire.influence 2.6459108E-9
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gdc.oaire.keywords Artificial neural network
gdc.oaire.keywords Urban rent
gdc.oaire.keywords Earthquakes
gdc.oaire.keywords Urban development
gdc.oaire.keywords Regression analysis
gdc.oaire.popularity 2.6037215E-9
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gdc.openalex.collaboration National
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