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http://dx.doi.org/10.7837/kosomes.2020.26.7.892

Prediction of Storm Surge Height Using Synthesized Typhoons and Artificial Intelligence  

Eum, Ho-Sik (GeoSystem Research Corporation)
Park, Jong-Jib (GeoSystem Research Corporation)
Jeong, Kwang-Young (Korea Hydrographic and Oceanographic Agency)
Park, Young-Min (GeoSystem Research Corporation)
Publication Information
Journal of the Korean Society of Marine Environment & Safety / v.26, no.7, 2020 , pp. 892-903 More about this Journal
Abstract
The rapid and accurate prediction of storm-surge height during typhoon attacks is essential in responding to coastal disasters. Most methods used for predicting typhoon data are based on numerical modeling, but numerical modeling takes significant computing resources and time. Recently, various studies on the expeditious production of predictive data based on artificial intelligence have been conducted, and in this study, artificial intelligence-based storm-surge height prediction was performed. Several learning data were needed for artificial intelligence training. Because the number of previous typhoons was limited, many synthesized typhoons were created using the tropical cyclone risk model, and the storm-surge height was also generated using the storm surge model. The comparison of the storm-surge height predicted using artificial intelligence with the actual typhoon, showed that the root-mean-square error was 0.09 ~ 0.30 m, the correlation coefficient was 0.65 ~ 0.94, and the absolute relative error of the maximum height was 1.0 ~ 52.5%. Although errors appeared to be somewhat large at certain typhoons and points, future studies are expected to improve accuracy through learning-data optimization.
Keywords
Typhoon; Storm surge height; TCRM; Synthesized Typhoons; Artificial intelligence;
Citations & Related Records
Times Cited By KSCI : 8  (Citation Analysis)
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