Multiclass support vector classification to estimate typhoon rainfall distribution

研究成果: Article同行評審

10 引文 斯高帕斯(Scopus)


The prediction of typhoon rainfalls provides important information for mitigating disasters. Different from models based on regression, this study proposes a classification methodology for typhoon rainfall estimation. A multiclass support vector classification with a one-against-one scheme is applied to develop the model. Using important typhoon characteristics, including the minimum central pressure, maximum central wind velocity, cyclonic radius and moving track as input variables, the multiclass classification model is able to predict the classes of rainfall depth, duration and type. The methodology combines the predicted classes of three rainfall parameters to estimate typhoon rainfall distribution. Calibration and validation results pertaining to data from 98 typhoon rainfall events in Alishan, Taiwan, show the ability of the proposed classification methodology to estimate typhoon rainfall distribution. Moreover, the proposed typhoon rainfall estimation model can potentially be updated into a real-time forecasting model by including relevant variables.

頁(從 - 到)110-121
期刊Disaster Advances
出版狀態Published - 2013 10月

All Science Journal Classification (ASJC) codes

  • 地理、規劃與發展
  • 安全、風險、可靠性和品質
  • 環境科學(雜項)
  • 地球與行星科學(雜項)


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