TY - GEN
T1 - Proposal and Evaluation of Prediction of Pavement Rutting Depth by Recurrent Neural Network
AU - Okuda, Tomoyuki
AU - Suzuki, Kouyu
AU - Kohtake, Naohiko
N1 - Funding Information:
ACKNOWLEDGMENT This research was funded by NEC. And we used precious pavement condition survey history data of Kawasaki City. We want to express our sincere gratitude for Kawasaki City.
Publisher Copyright:
© 2017 IEEE.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2017/11/15
Y1 - 2017/11/15
N2 - This paper describes a method of predicting the rutting depth by introducing Adam and dropout into MLP of neural network and GRU of recurrent neural net that can handle time series data. We built a model to predict the current rutting depth from the past rutting 3 years ago. We compared RMSE with the multiple regression model (MLR), which is most frequently used as a regression problem for the time variation of rutting depth. As a result, RMSE decreased in the order of MLR, MLP, GRU. The difference between GRU and RMSE of MLR was about 10%.
AB - This paper describes a method of predicting the rutting depth by introducing Adam and dropout into MLP of neural network and GRU of recurrent neural net that can handle time series data. We built a model to predict the current rutting depth from the past rutting 3 years ago. We compared RMSE with the multiple regression model (MLR), which is most frequently used as a regression problem for the time variation of rutting depth. As a result, RMSE decreased in the order of MLR, MLP, GRU. The difference between GRU and RMSE of MLR was about 10%.
KW - Machine learning
KW - Pavement condition survey
KW - Recurrent neural network
KW - Road management
UR - http://www.scopus.com/inward/record.url?scp=85040550726&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85040550726&partnerID=8YFLogxK
U2 - 10.1109/IIAI-AAI.2017.177
DO - 10.1109/IIAI-AAI.2017.177
M3 - Conference contribution
AN - SCOPUS:85040550726
T3 - Proceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017
SP - 1053
EP - 1054
BT - Proceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017
A2 - Hashimoto, Kiyota
A2 - Fukuta, Naoki
A2 - Matsuo, Tokuro
A2 - Hirokawa, Sachio
A2 - Mori, Masao
A2 - Mori, Masao
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017
Y2 - 9 July 2017
ER -