AN ANN APPROACHES ON ESTIMATING EARTHQUAKE PERFORMANCES OF EXISTING RC BUILDINGS

被引:16
作者
Arslan, M. H. [1 ]
Ceylan, M.
Koyuncu, T. [2 ]
机构
[1] Selcuk Univ, Fac Engn, Dept Civil Engn, TR-42075 Konya, Turkey
[2] Seydisehir Municipal Konya, Konya, Turkey
关键词
Earthquake performance; reinforced concrete; artificial neural network; PROBABILISTIC NEURAL-NETWORK; ACTIVE RESPONSE CONTROL; SEISMIC VULNERABILITY; PREDICTION; CONCRETE; BRIDGES;
D O I
10.14311/NNW.2012.22.027
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 R,C 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.
引用
收藏
页码:443 / 458
页数:16
相关论文
共 30 条
[1]   RELATIONSHIP BETWEEN VARIABLE SELECTION AND DATA AUGMENTATION AND A METHOD FOR PREDICTION [J].
ALLEN, DM .
TECHNOMETRICS, 1974, 16 (01) :125-127
[2]  
[Anonymous], 1998, TEC 1998
[3]  
[Anonymous], 2001, THESIS
[4]  
[Anonymous], 1996, ATC 40 SEISMIC EVALU
[5]  
[Anonymous], 1988, FEMA 155
[6]  
[Anonymous], 1994, Neural networks: a comprehensive foundation
[7]   Prediction of force reduction factor (R) of prefabricated industrial buildings using neural networks [J].
Arslan, M. Hakan ;
Ceylan, Murat ;
Kaltakci, M. Yasar ;
Ozbay, Yueksel .
STRUCTURAL ENGINEERING AND MECHANICS, 2007, 27 (02) :117-134
[8]   Predicting of torsional strength of RC beams by using different artificial neural network algorithms and building codes [J].
Arslan, M. Hakan .
ADVANCES IN ENGINEERING SOFTWARE, 2010, 41 (7-8) :946-955
[9]   An evaluation of effective design parameters on earthquake performance of RC buildings using neural networks [J].
Arslan, M. Hakan .
ENGINEERING STRUCTURES, 2010, 32 (07) :1888-1898
[10]  
Arslan MH, 2009, NAT HAZARD EARTH SYS, V9, P967