A forecast model for the ice thickness is developed using winter ice thickness data observed in Zhangye National Wetland Park watershed and surface air temperature and ground temperature data observed in Zhangye meteorological station from December 2011 to March 2012. This model is based on BP neural network which can approximate any nonlinear function. The forecasting skill of this model is validated by comparing the forecasted ice thicknessresults with the observed ones. The results show that: The frozen thickness of forecasting model is able to have comparatively ideal forecasting effect to frozen thickness, mobile frozen water area thickness forecasting history intends to jointly lead height to amount to 96.8%, the model tries reporting accurate rate for 85.7%, motionless frozen water area thickness forecast history intends to jointly lead amounting to 87.8%, the model tries reporting accurate rate for 80.0%. They have very good actual application value. It is function index accords with actual request. This forecasting model based on BP neural network is of good performance in forecasting the ice thickness.
LIU Honglan
,
ZHANG Junguo
,
QUE Longkai
,
ZHENG Xuejin
,
BAO Jiazhi
. Forecasting Model for Ice Thickness in Zhangye National Wetland Park Watershed Based on BP Neural Network[J]. Plateau Meteorology, 2014
, 33(3)
: 832
-837
.
DOI: 10.7522/j.issn.1000-0534.2013.00051
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