南京农业大学学报2011，Vol.34Issue(3)：61-66,6.
基于小波分解的害虫发生非平稳时间序列分析和预测
Analysis and forecasting for non-stationary time series of pest occurrence degree based on wavelet decomposition
摘要
Abstract
Wavelet decomposition was applied to analyze and forecast for non-stationary time series of pest occurrence degree. The non-stationary time series was decomposed into several stationary components with wavelet decomposition. Then, every stationary component was analyzed by auto-regressive moving average method and a model was established. Finally,the models of all stationary components were combined to obtain the model of the original non-stationary time series. The occurrence degree data series of Ostriniafurnacalis in Yantai from 1959 to 2004 was used to establish forecasting model,and the data from 2005 to 2009 was used to test the model. The test result showed that the forecasting accuracy of five years reached satisfying 80％.关键词
小波分解/多分辨率分析/非平稳时间序列/玉米螟/预测Key words
wavelet decomposition/ multi-resolution analysis/ non-stationary time series/ Ostrinia furnacalis/ forecasting分类
农业科技引用本文复制引用
朱军生,翟保平,刘英智..基于小波分解的害虫发生非平稳时间序列分析和预测[J].南京农业大学学报,2011,34(3):61-66,6.基金项目
国家973计划项目(2006CB102007) （2006CB102007）
国家科技支撑计划项目(2006BAD08A01) （2006BAD08A01）
