Open AccessData Prediction Model Based on LSTM Neural Network in Bridge Health Monitoring System
Author(s) -
Shihui Xiao,
Shengfang Qiao,
Hang Chen,
Xi Liu,
Yue Li,
Mengxiong Tang,
Hesong Hu,
Gaotang Li
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/668/1/012068
Subject(s) - bridge (graph theory) , artificial neural network , computer science , artificial intelligence , machine learning , process (computing) , data mining , medicine , operating system
The abnormal value was common in bridge health monitoring system. The prediction model based on LSTM neural network in bridge health monitoring system was studied in this paper. The modeling process was discussed about LSTM neural network model. The LSTM neural network model was also used to analysis the actual data in bridge. The results indicated that the prediction accuracy of LSTM model was high. Thus, the LSTM neural network could be used to analyze and predict data in bridge monitoring system.