摘要
时序数据在时间维度上存在着很强的时间相关性,在时序预测中,利用时序数据的时间相关性特点,构造了一种适用于时序数据预测的时序核函数,实现了将时间相关性融合于支持向量机,并通过人工数据和真实数据验证了时序核函数解决时序预测问题的有效性,并与传统核函数相比具有较好的泛化能力。
It is well known that there is high time correlation among time series data.This paper presented a new kernel function adapted in prediction for time series data,which incorporated the time correlation of time series into Support Vector Machine(SVM).Simulation experiments were performed to test the robustness of the findings on artificial stimuli and field data,which demonstrated that the presented kernel function can help to improve the fitting effect and obtain better generalization performance by comparing with the traditional kernel function of SVM.
出处
《计算机仿真》
CSCD
北大核心
2012年第3期29-32,48,共5页
Computer Simulation
关键词
支持向量机
时间相关性
核函数
Support vector machine(SVM)
Time correlation
Kernel function