Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Quarterly Journal of Applied Meteorology》 2004-03
Add to Favorite Get Latest Update

A NEW METHOD FOR NON-LINEAR CLASSIFY AND NON-LINEAR REGRESSION Ⅱ: APPLICATION OF SUPPORT VECTOR MACHINE TO WEATHER FORECAST

Feng Hanzhong (Chengdu Meteorological Center, Chengdu 610071) Chen Yongyi (Training Center of China Meteorological Administration, Beijing 100081)  
A novel weather forecast method using the support vector machine (SVM) is introduced. Both of SVM model of area rainfall categorical forecast of 15 mm excess and SVM model of single-station temperature regression in Sichuan basin are built upon ECMWF analysis fields of 500 hPa height, 850 hPa temperature, and sea level pressure from April to September through 1990-2000. Extensive experiments are performed with performances evaluated by the Threat Scores (TS) or Correlation Coefficient. Empirical results demonstrate much improved performance compared with those given by standard statistic analysis and forecast methods.
【Fund】: 国家自然科学基金资助 ( 60 0 72 0 0 6)
【CateGory Index】: O235
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved