Artificial Neural Networks and Microtremor Measurements in Estimating Peak Ground Acceleration at Main Lines of Kaohsiung Mass Rapid Transit, Taiwan

Publish Year: 1382
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:

SEE04_SF22

تاریخ نمایه سازی: 10 آبان 1384

Abstract:

Peak ground acceleration is a very important factor, which must be considered in construction site for analyzing the potential damage resulting from earthquake. The actual records by seismometer at stations related to the site may be taken as a basis, but a reliable estimating method may be useful for providing more detailed information of the strong motion characteristics. Therefore, the purpose of this study is by using back-propagation neural networks to develop a model for estimating peak ground acceleration at two main lines of Kaohsiung Mass Rapid Transit in Taiwan. In addition, the microtremor measurements with Nakamura transformation technique are taken to further validate the estimations. Three neural networks models with different inputs including epicentral distance, focal depth and magnitude of the earthquake records are trained and the output results are compared with available nonlinear regression analysis. The comparisons showed that the present neural networks model has a better performance than that of the other methods, as the calculation results are more reasonable and closer to the actual seismicrecords. Besides, the distributions of estimating peak ground acceleration from both of computations and measurements may provide valuable information from theoretical and practical standpoints.

Authors

Tienfuan Kerh

Professor, Department of Civil Engineering, National Pingtung University of Science and Technology, Pingtung ۹۱۲۰۷, Taiwan

David Chu

Graduate student of Civil Eng., NPUST, Pingtung, Taiwan,

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  • H. Adeli (2001).، Neural Networks in Civil Engineering: 1989-2000, Computer-A ...
  • L. Bodri (2000).، Prediction of Extreme Precipitation Using a Neural ...
  • CTCI Corporation (1991). 4Boring Test Report On Major Sections of ...
  • C. Gutierrez, S.K. Singh (1992). 40A Site Effect Study in ...
  • S. Ivanovic, M.D. Trifunac, M.I. Tlodorovska (2000).، 0Ambient Vibration Tests ...
  • T. Kerh, L.Y. Chen, J.H. Lee (1996). *Analysis of Soil ...
  • T. Kerh, J.H. Lee, L.Y. Chen (1996).، Estimation of Strong ...
  • T. Kerh, Y.C. Yee (2000). 4Analysis of a Deformed Three- ...
  • J. Lermo, F.J. Chavez -Gaircia (1994). 40Are Microtremors Useful in ...
  • Earthquake Study for Design؛ .(1993) 1 1. C.H. Loh, R.Y. ...
  • Amplification Based on Seismometer Aray and Soil؛، .(1992) 12. L. ...
  • K.F. Ma (1999).، :Teleseismic and Near Source Strong Motion Waveforms ...
  • Surface Layer Thickness and the Shearing Wave Theء، .(1990) 14. ...
  • P.C. Pandey, S.V. Barai (1995). *Multilayer Perceptron in Damage Detection ...
  • T. Suzuki, Y. Adachi, M. Tanaka (1995). *Application of Microtremor ...
  • C.P. Tsai, J.N. Shen, T. Kerh (1999).، Wave Forecasting Using ...
  • User Manual (1995). *Carry Style Vibrator SPC-35F?, System Technology Engineering ...
  • نمایش کامل مراجع