Visual analysis of tropical cyclone trajectory prediction

Cui Xie; Hao Yang; Guangxiao Ma; Junyu Dong

doi:10.1117/12.2302802

10 April 2018 Visual analysis of tropical cyclone trajectory prediction

Cui Xie, Hao Yang, Guangxiao Ma, Junyu Dong

Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 106155H (2018) https://doi.org/10.1117/12.2302802
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China

Abstract

In this paper, we propose a visual interactive analysis approach for tropical cyclone trajectory prediction based on the support vector machine (SVM) regression method. We design a visual analysis interface that supports training data selection, model parameters adjustment and the visual assessment of model quality. This visual analysis approach can facilitate the prediction process and enable users to predict tropical cyclone trajectory easily. A case study with real data demonstrates the effectiveness of our approach.

Citation Download Citation

Cui Xie, Hao Yang, Guangxiao Ma, and Junyu Dong "Visual analysis of tropical cyclone trajectory prediction", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106155H (10 April 2018); https://doi.org/10.1117/12.2302802

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