支持向量机的混沌序列预测模型及在径流中应用

混沌和支持向量机理论为研究复杂多变的非线性水文时间序列开辟了新的途径。给出了应用支持向量机回归原理的混沌时间序列非线性的预测建模的思路、特点及关键参数的选取。根据重构相空间理论对月径流过程进行相空间的重构,探讨了支持向量机混沌时间序列非线性预测模型在月径流预测中的应用,在支持向量机建模过程中引入了经向基核函数,简化了非线性问题的求解过程。实例表明,该模型能较好地处理复杂的水文数据序列,且有较好的预测精度。

The prediction model of chaotic series based on support vector machine and its applica tion to runoff

Chaos and support vector machine theory has opened up a new route to study complicated and changeable non-linear hydrology time series.Applying the Chaos and non-linear time series based on the support vector machine regression principle,this paper proposes a method and its characteristic and the choosing of key parameters to forecast and set up models.According to Phase Space Reconstruction theory carry on reconstruction of Phase Space to monthly surface flow course,have discussed that probed into the non-linear prediction model of time series of Chaos of the support vector machine application in the monthly surface flow,have introduce it through to the nuclear function of the base in the course of setting up the model of support vector machine,has simplified the course of solving the non-linear problems.The instance indicates that the model can deal with the complicated hydrology data array well,and there is the good prediction precision.