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Visual analysis of tropical cyclone trajectory prediction
Author(s): Cui Xie; Hao Yang; Guangxiao Ma; Junyu Dong
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Paper 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.

Paper Details

Date Published: 10 April 2018
PDF: 5 pages
Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106155H (10 April 2018); doi: 10.1117/12.2302802
Show Author Affiliations
Cui Xie, Ocean Univ. of China (China)
Hao Yang, Xi'an Univ. of Technology (China)
Guangxiao Ma, Ocean Univ. of China (China)
Junyu Dong, Ocean Univ. of China (China)


Published in SPIE Proceedings Vol. 10615:
Ninth International Conference on Graphic and Image Processing (ICGIP 2017)
Hui Yu; Junyu Dong, Editor(s)

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