Development of Water Level Prediction Improvement Method Using Multivariate Time Series Data by GRU Model

Development of Water Level Prediction Improvement Method Using Multivariate Time Series Data by GRU Model

The methods for improving the accuracy of water level prediction were proposed in this study by selecting the Gated Recurrent Unit (GRU) model, which is effective for multivariate learning at the Paldang Bridge station in Han River, South Korea, where the water level fluctuates seasonally. The hydro...

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Bibliographic Details
Main Authors: Kidoo Park, Yeongjeong Seong, Younghun Jung, Ilro Youn, Cheon Kyu Choi
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Water
Subjects:
water level
GRU
meteorological data
multivariate learning
correlation
meteorological observatory
Online Access:https://www.mdpi.com/2073-4441/15/3/587

Internet

https://www.mdpi.com/2073-4441/15/3/587

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