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صفحه اصلی
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اولین همایش بین المللی هوش مصنوعی
Damage Prediction of RC Columns Using Machine Learning Algorithms
نویسندگان :
Amirali Abdolmaleki
1
Shima Mahboubi
2
1- Bachelor of civil engineering student
2- Assistant Professor at Civil Engineering Department of Shahid Beheshti University
کلمات کلیدی :
Machine learning algorithm،RC Bridge pier،Damage states،Seismic performance
چکیده :
Performance-based design of bridges requires prediction of different damage states of components. (RC) piers are key components in bridge system, which may experience severe damages during earthquakes. Therefore, seismic damage assessment of RC bridges depends strongly on predicting failure modes RC piers. Using machine learning for damage evaluation of structures is becoming increasingly popular in earthquake engineering. This study implements three different machine learning techniques to capture different damage limit states of RC bridge piers under seismic loading. For this purpose, three machine learning techniques including K-Nearest Neighbors (KNN), Artificial Neural Networks (ANNs) and decision tree regressions were utilized for predicting four damage states of a RC bridge piers tested experimentally under seismic excitations based on drift limits. The efficiency of the three algorithms in damage prediction of RC piers were compared.
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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 41.1.5