Significance of rent attributes in prediction of earthquake damage in Adapazari

Title:

Significance of rent attributes in prediction of earthquake damage in Adapazari

Creator:

Tyfur, Gökmen, Bektas, Birkan, and Duvarci, Yavuz

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:eab63996-8e64-4036-bdbf-e9ed37e3835e
uuid:eab63996-8e64-4036-bdbf-e9ed37e3835e
doi:10.14311/NNW.2014.24.036

Subject:

Earthquakes, urban rent, urban development, regression analysis, and artificial neural network

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

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.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2014 Volume:24 | Number:6

Harvested from:

CDK

Metadata only:

false