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山东大学学报(工学版) ›› 2011, Vol. 41 ›› Issue (3): 23-30.

• 机器学习与数据挖掘 • 上一篇    下一篇

多输出支持向量回归机在依赖时间的变分不等式中的应用

赵燕燕, 范丽亚   

  1. 聊城大学数学科学学院, 山东 聊城 252059
  • 收稿日期:2011-01-25 出版日期:2011-06-16 发布日期:2011-01-25
  • 作者简介:赵燕燕(1986- ),女,山东肥城人,硕士研究生,主要研究方向为数据挖掘,变分不等式理论及其应用.Email:zhaoyan97531@126.com
  • 基金资助:

    国家自然科学基金资助项目(10871226); 山东省自然科学基金资助项目(ZR2009AL006)

The application of a multi-output support vector regression
machine in time-dependent variational inequalities

ZHAO Yanyan, FAN Liya   

  1. School of Mathematics,  Liaocheng University, Liaocheng 252059, China
  • Received:2011-01-25 Online:2011-06-16 Published:2011-01-25

摘要:

支持向量回归技术广泛用于解决单输出回归问题,但现实中存在更多的是多输出的情形。为更好地解决多输出回归问题,在单输出支持向量回归机的基础上,通过并行运算推广得到一种多输出支持向量回归机,并在动态交通均衡问题的背景下,求解依赖时间的变分不等式问题。实验表明与单输出支持向量回归算法和线性插值比较,多输出支持向量回归算法具有更快的计算速度和更好的拟合效果。文中给出的多输出支持向量回归机不仅推进了多输出支持向量回归机的研究,而且为解决依赖时间的变分不等式问题提供了一种新思路。

关键词:  , 线性规划支持向量机, 多输出支持向量回归机, 依赖时间的变分不等式, 动态交通均衡问题

Abstract:

The method of a support vector regression machine was  developed for solving single output regression problems. However many questions belong to multioutput regression in practice. In order to deal with these  problems, the support vector regression machine was extended to multioutput by parallel operation. And it was applied to solve the problem of timedependent variational inequalities which describe dynamic traffic equilibrium. The result of one experiment showed that it had faster calculation speed and better fitting effect than a singleoutput support vector regression machine and linear interpolation. The algorithm promoted the study of a multioutput support vector regression machine and provided a novel means to solve the problem of timedependent variational inequalities.
 

Key words: linear programming support vector regression machine, multi-output support vector regression machine(M-SVR), timedependent variational inequality, dynamic traffic equilibrium problem

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