安徽农业科学2011，Vol.39Issue(36)：22415-22419,5.
基于马尔可夫模型的南京市年降水量预测试验
Forecast Experiment of Nanjing Annual Precipitation Based on Markov Model
梅疏影1
作者信息
- 1. 南京信息工程大学大气环境与工程学院,江苏南京210044
- 折叠
摘要
Abstract
Given the uncertainties in the precipitation process, the forecast of long-term precipitation has always been a problem in meteorological field. Here through the use of smoothing to eliminate outliers and the classification of annual precipitation, a moving average Markov forecast model was established to carry out a trial forecast of Nanjing precipitation in 2009 and 2010. As shown by the results, the relative error between the forecasted value and measured value was 2. 17% in 2009 and 3.09% in 2010, the forecast precision was high. Moreover, in order to make up for a deficiency of moving average Markov model that it could not predict the year with extreme precipitation, the grey system was used to forecast the extreme rainfall years. Combination of both could better accomplish the forecasting of annual precipitation in Nanjing.关键词
滑动平均马尔可夫模型/年降水量/预测/灰色灾变系统Key words
Moving average Markov model/ Annual precipitation/ Forecast/ Grey system分类
天文与地球科学引用本文复制引用
梅疏影..基于马尔可夫模型的南京市年降水量预测试验[J].安徽农业科学,2011,39(36):22415-22419,5.
