根据时间序列近期数据较远期数据包含有更多未来信息的思想，对最小二乘支持向量机预测方法进行了扩展，得到了更具一般性的最小二乘支持向量机预测模型，给出了扩展后的预测模型具体算法。两个时间序列的预测实例表明，扩展后的预测方法获得了更好的预测效果，提升了最小二乘支持向量机预测方法的价值。

According to the theory that the present data contains more future information than historical data in time-series,the paper extends the prediction method of least square support vector machine and obtains a more general prediction model of least square support vector machine,and develops algorithm of the extended prediction model.Prediction examples of two time-series show that the extended model is more effective.Therefore it improves the value of the prediction method of least square support vector machine.

向小东（1973－），男，四川广安市人，博士，福州大学管理学院副教授，研究方向为系统预测与决策