| 在线多输出支持向量回归及在投资决策中的应用 |
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| 引用本文： | 胡根生,邓飞其. 在线多输出支持向量回归及在投资决策中的应用[J]. 华南理工大学学报(自然科学版), 2006, 34(6): 64-68 |
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| 作者姓名： | 胡根生 邓飞其 |
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| 作者单位： | 华南理工大学,自动化科学与工程学院,广东,广州,510640;华南理工大学,自动化科学与工程学院,广东,广州,510640 |
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| 基金项目： | 国家自然科学基金;广东省自然科学基金 |
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| 摘 要： | 提出一种在线多输出支持向量机回归算法：对新到达的样本，利用梯度下降算法，最小化预测结果的带正则项的即时风险，给出回归函数权系数和偏置的迭代公式，完成在线情况下的多输出回归预测．将该算法应用于投资决策，可以在线预测最优投资组合．仿真实验结果表明，该算法计算简单，工作量小，因而更容易实现．
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| 关 键 词： | 支持向量回归 多输出预测 在线学习 投资决策 |
| 文章编号： | 1000-565X（2006）06-0064-05 |
| 收稿时间： | 2005-06-27 |
| 修稿时间： | 2005-06-27 |
On-line Multi-Output Support Vector Regression and Its Application to Investment Decision |
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| Hu Gen-sheng,Deng Fei-qi. On-line Multi-Output Support Vector Regression and Its Application to Investment Decision[J]. Journal of South China University of Technology(Natural Science Edition), 2006, 34(6): 64-68 |
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| Authors: | Hu Gen-sheng Deng Fei-qi |
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| Affiliation: | College of Automation Science and Engineering, South China Univ. of Tech. , Guangzhou 510640, Guangdong, China |
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| Abstract: | An on-line multi-output support vector machine regression algorithm is proposed in this paper. By using the gradient descent algorithm to minimize the instantaneous regularized risk of prediction results, the iterative formulae of the weight coefficients and the bias of the regression function are obtained. Thus, the on-line multi-output regression prediction can be implemented for new arriving samples. The proposed algorithm is then applied to the investment decision to predict the optimal portfolio on line. Simulation results show that the proposed algorithm is easy to carry out because of its simple computation and small workload. |
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| Keywords: | support vector regression multl-output prediction on-line learning investment decision |
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