中文摘要：

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．

英文摘要：

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.