Water Level Forecasting in the Gamcheon River, Korea, Using TimeGPT

초록

To the best of our knowledge, this study is the first attempt to predict the water level of the Gamcheon River, Korea, using the large language model (LLM)-based TimeGPT. Our research shows that TimeGPT outperforms existing time- series models, including SARIMAX and DLinear. TimeGPT provides better prediction accuracy for short- and long-term forecasts under Nash-Sutcliffe efficiency scores. TimeGPT effectively captures water level changes by integrating rainfall data. Our approach provides insights into water resource management and flood prediction. © The Korean Institute of Intelligent Systems. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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