摘要
利用混沌和分形理论,对湖北省襄樊地区小麦条锈病受灾率进行了混沌识别研究,对其功率谱、主分量、关联维度、最大Lyapunov指数进行了分析。结果表明,小麦条锈病受灾率时间序列具有混沌特征,属于混沌时间序列。因此建议对小麦条锈病进行建模预测时,应主要采用非线性建模方法。
Forecast the disaster rate of crops is important, unfortunately, it is also difficult. Proving whether disaster rates are chaotic is useful for modeling. Based on the chaotic theory, there are several methods developed for the chaos identification at present. In this paper, power spectrum and PCA of the disaster rates are analyzed; correlation dimension and Lyapunov exponent are computed by the reconstruction of phase space, G-P algorithm and method of determining Lyapunov exponent from time series for identifying chaotic character of the time sequence, and the time sequence is proved to be chaotic indeed. So methods of modeling nonlinear systems can be used in modeling and forecasting the disaster rate of crops time sequence.
出处
《西北农林科技大学学报（自然科学版）》
CSCD
北大核心
2005年第9期63-67,共5页
Journal of Northwest A&F University(Natural Science Edition)
基金
湖北省教育厅科研项目(2001D69001)
关键词
小麦条锈病
受灾率时间序列
混沌识别
混沌特征
wheat stripe rust
the disaster rate of crops time sequence
chaos identification
chaotic character
