Sequential quadratic programming method was used, and optimal Pareto set with different weight values were obtained. 采用序列二次规划(QP)法对模型进行了优化求解,得到了不同权重值时的多目标优化解集。
The model solved a convex quadratic programming similar to standard support vector machine algorithm. 更新模型是求解一个与标准支持向量机具有类似的数学形式的凸二次规划(QP)问题。
This paper discusses a finite element model updating method based on sequence quadratic programming ( SQP ). 提出了一种利用通用有限元程序和数学软件进行有限元模型修正的方法。
In this paper, cubic spline theory and sequential quadratic programming are used for optimizing the initial reference path. 在粗略最短路径的基础上,应用三次样条曲线和序列二次规划(QP)的方法求解最优路径。
However, the training procedure of support vector machines amounts to solving a constrained quadratic programming. 然而,支持向量机的训练过程等价于求解一个约束凸二次规划(QP)。