Intelligent monitoring system on prediction of building damage index using neural-network

Telkomnika

Volumn 10, Issue 1, 2012, Pages 155-164

  Mardiyono, ^a   Suryanita, Reni ^b   Adnan, Azlan ^c  

^a Polytechnic Negeri Semarang   (Indonesia)

^b UNIVERSITY OF RIAU   (Indonesia)

^c UNIVERSITI TEKNOLOGI MALAYSIA   (Malaysia)

Author keywords

Artificial neural network; Building; Damage index; Intelligent; Monitoring

Indexed keywords

BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; BUILDINGS; DAMAGE DETECTION; DEEP NEURAL NETWORKS; EARTHQUAKES; FORECASTING; GEOPHYSICS; NEURAL NETWORKS; TALL BUILDINGS;

ACCURATE PREDICTION; COLLAPSE PREVENTION; DAMAGE INDEX; FEED-FORWARD AND BACK-PROPAGATION ALGORITHMS; INTELLIGENT; INTELLIGENT MONITORING SYSTEMS; NON-LINEAR METHODS; STRUCTURE ANALYSIS;

MONITORING;

EID: 84883603519     PISSN: 16936930     EISSN: 23029293     Source Type: Journal    
DOI: 10.12928/telkomnika.v10i1.773     Document Type: Article

References (16)

1. FEMA356 (2000). Prestandard and Commentary for The Seismic Rehabilitation of Buildings. Federal Emergency Management Agency. FEMA 356.
2. nd International Conference on Future Computer and Communication (ICFCC). Wuhan China. 2010; 3: i-xxiii.
3. Tugce K, Murat G, Selcen B. Artificial Neural Network to Predict Daylight Illuminance in Office Building. Building and Environment. 2009; 44(8): 1751-1757.
4. Jun-Jie W, Hui-Ying G, Ming-Qiong L. Seismic Damage Prediction of Multistory Building Using GIS and Artificial Neural Network. Sixth International Conference on Natural Computation (ICNC). Shandong China. 2010; 8: 1821-1824.
5. nd IEEE International Symposium on Intelligent Control. Singapore. 2007: 138-143.
6. nd IEEE International Conference on Information Management and Engineering (ICIME). Chengdu, China. 2010: 365-369.
7. Chen Y, Liu T, Liu W. Predictive Model of Artificial Neural Network for Earthquake Influence Analysis International Forum on Information Technology and Application (IFITA). Chengdu, China. 2009; 1: 20-23.
8. Wang J, Gao H, Xin J. Application of Artificial Neural Network and GIS in Urban Earthquake Disaster Mitigation. International Conference on Intelligent Computation Technology and Automation (ICICTA). Changsha, Hunan, China. 2010; 1: 726-729.
9. Lei S, Jin W. Application of Artificial Neural Network to Predict the Hourly Cooling Load of an Office Building. International Joint Conference on Computational Science and Optimization. Sanya, Hainan, China. 2009; 1: 528-530.
10. Li X, Ding L, Deng Y, Li I. Hybrid Support Vector Machine and ARIMA Model in Building Cooling Prediction. International Symposium on Computer, Communication, Control and Automation. Sanya, Hainan, China. 2009; 1: 528-530.
11. Ju H, Li JW. Application of Artificial Neural Network Approach for Intelligent Building in China. Fourth International Conference on Computer Sciences and Convergence Information Technology. Seoul, Korea. 2009; 1: 1320-1324.
12. Li Q, Xiaoying D. Research on Selection of Tall Building Structures Based on Artificial Neural Network. Sixth International Conference on Natural Computation (ICNC). Shandong China. 2010; 8: 1808-1811.
13. nd International Conference on Computer Engineering and Technology (ICCET). Chengdu China. 2010; 6: 184-187.
14. Chen XJ, Gao ZF, Wang W. Application of BP Artificial Neural Network in Structure Damage Identification. International Conference on Intelligent Computation Technology and Automation (ICICTA). Changsha, Hunan, China. 2010; 1: 733-737.
15. Jones TM. AI Application Programming. Massachusetts: Charles River Media, INC. 2003: 94-100.
16. Mardiyono, Suryanita R. Prediction of Building Condition after Earthquake Using Artificial Neural Network. Seminar Nasional Teknologi Informasi Komunikasi dan Industri (SNTIKI3). Pekan Baru, Riau, Indonesia. 2011: 47-55.