The Application of Artificial Neural Networks in Predicting Seismic response of RC Frames with masonry infills
Publish Year: 1390
نوع سند: مقاله کنفرانسی
زبان: English
View: 1,585
This Paper With 8 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
این Paper در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
SEE06_131
تاریخ نمایه سازی: 16 اردیبهشت 1390
Abstract:
The objective of this study is the application of artificial neural networks (ANN) in estimating seismic behavior of reinforced concrete (RC) frames with masonry infills. In the present research existing RC frames are modeled by changing number of bays, number of stories, infill thickness, existence of soft storey and infilled wall ratio (opening percentage). The capacity curve of all modeled frames is obtained using pushover analysis. Afterwards, base shear and roof displacement (ANN outputs) in target displacement (performance point) are calculated for three design spectral accelerations (moderate, high, very high seismic hazard region). Finally 855 data set are prepared, and a three-layer feed-forward neural network with 11 back propagation algorithms is trained in different structures and the best structure is obtained for each network using trial and error. The results indicate that the Levenberg-Marquart back propagation algorithm has the highest accuracy compared to other algorithms
Keywords:
Authors
I Kameli
M.sc, Dept. of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran,
m Miri
Assistant professor, Dept. of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran,
a Raji
M.Sc in Structural Engineering
f Bahrami
M.sc, Dept. of Mechanical Engineering, University of Sistan and Baluchestan, Zahedan, Iran
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :