Artificial Neural Network Application for Predicting Seismic Damage Index of Buildings in Malaysia

被引：13

作者：

Adnan, Azlan ^{[1
]}

Tiong, Patrick Liq Yee ^{[1
]}

Ismail, Rozaina ^{[2
]}

Shamsuddin, Siti Mariyan ^{[3
]}

机构：

[1] Univ Teknol Malaysia, Engn Seismol & Earthquake Engn Res E SEER, Johor Baharu, Malaysia

[2] Univ Teknol MARA, Fac Civil Engn, Johor Baharu, Malaysia

[3] Univ Teknol Malaysia, Dept Comp Graph & Multimedia, Johor Baharu, Malaysia

来源：

ELECTRONIC JOURNAL OF STRUCTURAL ENGINEERING | 2012年 / 12卷 / 01期

关键词：

Seismic performance of buildings; Artificial Neural Network; damage index of building;

D O I：

10.56748/ejse.12146

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

An effective, convenient and reliable intelligent seismic evaluation system for buildings in Malaysia has been developed in this study by using Back-Propagation Artificial Neural Network (ANN) algorithm. A total of forty one buildings with 164 sets of input data spreading throughout Peninsular and East Malaysia were chosen and analyzed using IDARC-2D finite element software under seismic loading at peak ground accelerations of 0.05g, 0.10g, 0.15g and 0.20g respectively. Non-linear dynamic analysis was performed in order to obtain the damage index of each building. The ANN algorithm comprising 15 hidden neurons with 1 hidden layer outperformed other combinations in predicting the damage index of buildings with accuracy statistical value of 93% in testing phase as well as 75% in validation stage. From the results, the ANN system is suitable to be used for predicting the seismic behaviour of their buildings at any given time.

引用

页码：1 / 9

页数：9

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