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

• Published in: Electronic journal of structural engineering Vol. 12; pp. 1 - 9
• Main Authors: Azlan Adnan, Patrick Liq Yee Tiong, Rozaina Ismail, Siti Mariyan Shamsuddin
• Format: Journal Article
• Language: English
• Published: Electronic Journals for Science and Engineering - International 01.01.2012
• Subjects: Artificial Neural Network; Damage index of building; Seismic performance of buildings
• ISSN: 1443-9255; 1443-9255
• DOI: 10.56748/ejse.12146

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.