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Applying a Machine Learning Technique to Classification of Japanese Pressure Patterns Cover

Applying a Machine Learning Technique to Classification of Japanese Pressure Patterns

By: H Kimura,  H Kawashima,  H Kusaka and  H Kitagawa  
Open Access
|Apr 2009

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: https://doi.org/10.2481/dsj.8.S59 | Journal eISSN: 1683-1470
Language: English
Published on: Apr 1, 2009
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2009 H Kimura, H Kawashima, H Kusaka, H Kitagawa, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.