ONE YEAR VERIFICATION OF WAVE PREDICTIONS BY DEEP LEARNING USING XCEPTION-Reference-Cited by-同舟云学术

ONE YEAR VERIFICATION OF WAVE PREDICTIONS BY DEEP LEARNING USING XCEPTION

Published:2020 Issue:2 Volume:76 Page:I_1213-I_1218
ISSN:1883-8944
Container-title:Journal of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering)
language:en
Short-container-title:Journal of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering)

Author:

TOM Tracey H. A.¹,IKEMOTO Ai²,MASE Hajime³,KIM Sooyoul⁴,TAKEDA Masahide⁵,KAWASAKI Koji⁶

Affiliation:

1. Hydro Technology Institute, Co., Ltd.

2. HOKUULA Co. Ltd.

3. Disaster Prevention Research Institute, Kyoto University

4. Social Systems and Civil Engineering, Tottori University

5. Research and Development Center, TOA Corporation

6. Hydro Technology Institute, Co., Ltd., Meijo University, Osaka University and Osaka City University

Publisher

Japan Society of Civil Engineers

Link

https://www.jstage.jst.go.jp/article/kaigan/76/2/76_I_1213/_pdf

Reference9 articles.

1. 1) Booij, N, Ris, R. C. and Holthuijsen, L. H. : A third generation wave model for coastal regions: 1. 598 Model description and validation, Jour. Geophys. Res., Vol. 104, Issue C4, pp. 67649-7666, 599, 1999.

2. 2) Mase, H., Sakamoto, M. and Sakai, T. : Neural network for stability analysis of rubble-mound breakwaters, J. Waterway, Port, Coastal, and Ocean Eng., ASCE, Vol. 121, No. 6, pp. 294-299, 1995.

3. 3) Tom, H. A., Mase, H., Ikemoto, A., Saitoh, T., Kawasaki, K., Takeda, M. : Wave Prediction by Neural Network Using atmospheric Pressure and Wind Speeds, Journal of JSCE, Ser.B2, Coastal Eng., Vol. 74, No. 2, pp. I_691-I_696, 2018.

4. 4) TensorFlow: Large-scale machine learning on heterogeneous systems, 2015. Software available from tensorflow.org.

5. 5) Tom, H. A., Ikemoto, A., Mase, H., Kawasaki, K., Takeda, M., Kim, S. : Wave Prediction in the Sea of Japan by Deep Learning Using Meteorological Data, Journal of JSCE, Ser.B2, Coastal Eng., Vol. 75, No. 2, pp. I_145-I_150, 2019.

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