Application of Support Vector Machine Regression Method in Weather Forecast

The support vector machine (SVM) regression principle and its application to weather forecast are introduced. By using ECMWF analysis fields of 500hPa height, 850hPa temperature, and sea level pressure from January to September through 1990—2000, the SVM regression models are built on daily average temperature, maximum temperature, minimum temperature of five typical stations in Deyang. The performances of these models are evaluated.

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