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Research Papers

Applying a Machine Learning Technique to Classification of Japanese Pressure Patterns

Authors:

H Kimura ,

Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Ibaraki, Japan
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H Kawashima,

Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Ibaraki, Japan Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
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H Kusaka,

Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
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H Kitagawa

Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Ibaraki, Japan Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
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Abstract

In climate research, pressure patterns are often very important. When a climatologists need to know the days of a specific pressure pattern, for example "low pressure in Western areas of Japan and high pressure in Eastern areas of Japan (Japanese winter-type weather)," they have to visually check a huge number of surface weather charts. To overcome this problem, we propose an automatic classification system using a support vector machine (SVM), which is a machine-learning method. We attempted to classify pressure patterns into two classes: "winter type" and "non-winter type". For both training datasets and test datasets, we used the JRA-25 dataset from 1981 to 2000. An experimental evaluation showed that our method obtained a greater than 0.8 F-measure. We noted that variations in results were based on differences in training datasets.
DOI: http://doi.org/10.2481/dsj.8.S59
How to Cite: Kimura, H. et al., (2009). Applying a Machine Learning Technique to Classification of Japanese Pressure Patterns. Data Science Journal. 8, pp.S59–S67. DOI: http://doi.org/10.2481/dsj.8.S59
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Published on 01 Apr 2009.
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