An ANN approaches on estimating earthquake performances of existing RC buildings

Title:

An ANN approaches on estimating earthquake performances of existing RC buildings

Creator:

Arslan, M. H., Ceylan, M., and Koyuncu, T.

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:4086da14-293d-4b3c-85a3-68d5885a537a
uuid:4086da14-293d-4b3c-85a3-68d5885a537a
doi:10.14311/NNW.2012.22.027

Subject:

Earthquake performance, reinforced concrete, and artificial neural network

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

This study aims at developing an artificial intelligence-based (ANN based) analytical method to analyze earthquake performances of the reinforced concrete (RC) buildings. In the scope of the present study, 66 real RC buildings with four to ten storeys were subject to performance analysis according to 19 parameters considered effective on the performance of RC buildings. In addition, the level of performance of these buildings in case of an earthquake was determined on the basis of the 4-grade performance levels specified in Turkish Earthquake Code-2007 (TEC-2007). Thus, an output performance data group was created for the analyzed buildings, in accordance with the input data. Thanks to the ANN-based fast evaluation algorithm mentioned above and developed within the scope of the proposed project study, it will be possible to make an economic and rapid evaluation of four to ten-storey RC buildings in Turkey with great accuracy (about 80%). Detection of post-earthquake performances of RC buildings in the scope of the present study will facilitate reaching important results in terms of buildings, which will be beneficial for Civil Engineers of Turkey and similar countries.

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 | 2012 Volume:22 | Number:5

Harvested from:

CDK

Metadata only:

false