Recurrent Neural Network Predictions for Water Levels at Drainage Pumping Stations in an Agricultural Lowland

Author:

KIMURA Nobuaki1,YOSHINAGA Ikuo1,SEKIJIMA Kenji1,AZECHI Issaku1,KIRI Hirohide2,BABA Daichi3

Affiliation:

1. Institute for Rural Engineering, National Agriculture & Food Research Organization

2. Agriculture, Forestry and Fisheries Research Council, Ministry of Agriculture, Forestry and Fisheries

3. ARK Information Systems, Inc.

Publisher

Japan International Research Center for Agricultural Sciences

Subject

Agronomy and Crop Science,Animal Science and Zoology,Ecology,Biotechnology

Reference25 articles.

1. Dozat, T. (2016) Incorporating Nesterov momentum into Adam. In proceedings of the International Conference on Learning Representations (ICLR) 2016.

2. Duchi, J. et al. (2011). Adaptive subgradient methods for online learning and stochastic optimization. J Mach. Learn. Res., 12, 2121-2159.

3. Fischer, T. & Krauss, C. (2018) Deep learning with long shortterm memory networks for financial market predictions. Eur. J. Oper. Res., 270, 654-669.

4. Geisser, S. (1993) Predictive inference: An introduction, Monographs on statistics and applied probability 55. Chapman and Hall, NY, USA.

5. Gers, F. A. et al. (2000) Learning to forget: continual prediction with LSTM. Neural Comput., 12, 2451-2471. DOI: https://doi.org/10.1162/089976600300015015.

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