Multiple-Input Convolutional Neural Network Model for Large-Scale Seismic Damage Assessment of Reinforced Concrete Frame Buildings

Multiple-Input Convolutional Neural Network Model for Large-Scale Seismic Damage Assessment of Reinforced Concrete Frame Buildings

This study introduces a multiple-input convolutional neural network (MI-CNN) model for the seismic damage assessment of regional buildings. First, ground motion sequences together with building attribute data are adopted as inputs of the proposed MI-CNN model. Second, the prediction accuracy of MI-C...

Full description

Bibliographic Details
Main Authors: Chen Xiong, Jie Zheng, Liangjin Xu, Chengyu Cen, Ruihao Zheng, Yi Li
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Applied Sciences
Subjects:
seismic damage assessment
multiple-input convolutional neural network
machine learning
nonlinear time history analysis
seismic response
Online Access:https://www.mdpi.com/2076-3417/11/17/8258

Internet

https://www.mdpi.com/2076-3417/11/17/8258

Similar Items