• In Chapter 7, we study stability of second-order derivatives in vector optimization problems.

    在第七章里,讨论向量优化问题的二阶导数的稳定性。

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  • In this paper, we study the scalarization over Euclidean Jordan algebra vector optimization problem.

    本文主要研究欧几里德若当代数向量优化的谱标量化。

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  • Vector optimization problems with control parametra are considered under generalized convexity condition.

    在广义凸条件下,研究了带控制参量的向量优化问题。

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  • A new proposal for multipoint rotate-vector optimization is presented based on the basic rotate-vector method.

    在基本旋转矢量法的基础上,提出了多点旋转矢量优化方法。

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  • Optimality conditions for vector optimization problem to attain strictly efficient solutions are considered in the paper.

    本文研究向量优化问题在严有效解意义下的最优性条件。

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  • In this paper, we mainly consider the existence of the generalized weakly efficient solution for Vector Optimization Problem.

    利用此定理,得到了带广义不等式约束的向量优化问题的最优性必要条件和充分条件。

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  • Aim to study the cone subdifferential of the cone efficient solution sets for set valued vector optimization problem with perturbed order.

    目的研究锥扰动集值映射向量优化问题锥有效解的锥次可微性。

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  • Finally, the optimality conditions for vector optimization problems with set valued maps with equality and inequality constraints are obtained with it.

    最后,利用择一性定理,获得了含不等式和等式约束的广义次似凸集值映射向量最优化问题的最优性条件。

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  • As its applications, the continuity of solution mappings for a class of parametric vector optimization problem and parametric vector variational inequality is obtained.

    作为应用,得到一类参数向量优化问题和参数向量变分不等式的解的连续性。

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  • In this paper, We prove the existence of a weak minimum for constrained vector optimization problem by making use of vector variational-like inequality and semi-preinvex functions.

    本文通过使用向量似变分不等式和半预不变凸函数来证明约束向量优化的弱极小值的存在性。

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  • Under the conditions of Partial ic-convex like Maps, optimality necessary conditions of weak efficient solutions for vector optimization problems with equality and inequality constraints are obtained.

    在部分生成锥内部凸-锥-凸映射下,得到了既有等式约束又有不等式约束的向量优化问题弱有效解的最优性必要条件。

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  • This class, taught by the guest speaker, is devoted to the optimization problems underlying the implementation of Support Vector Machines.

    这堂课将由授课的特别来宾讲解构成向量机执行基本原理的最佳化问题运用。

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  • Optimization techniques for the sparse matrix vector multiplication are adopted in programming.

    编程中采用了稀疏矩阵向量相乘的优化技术。

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  • The conclusion is given through simulation that the overall principle to optimization is orthogonalization of the sensitivity optimal vector.

    结论是:多光谱系统灵敏度优化向量的正交化设计是系统光谱图像获取的必要要求;

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  • On the conditions that vector objective function is like-convex and quasi-convex, we obtain the connectedness of G-proper efficient solution set of the multiobjective optimization problem.

    在此基础上,得到了向量目标函数既是似凸又是拟凸的多目标最优化问题的G-恰当有效解集是连通的结论。

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  • The optimization of solution is carried out by Iterated Conditional Mode (ICM) method. The initial segmentation label fields is gotten using vector histogram.

    最小能量的优化求解用迭代条件模式(ICM)方法,初始分割标记场用矢量直方图法得到。

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  • SIMD optimization is very similar to traditional automatic vectorization for vector processors.

    这种优化和传统的针对向量处理器的自动向量化非常类似。

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  • After studying on modeling theories of SVM and the parameter optimization of SVM, the Least Squares Support Vector Machines tool LSSVM.

    在研究支持向量机的建模理论和参数优化方法的基础上,将最小二乘法支持向量机工具LSSVM。

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  • Based on summarizing the existing algorithms of transferring vector data to raster data, an optimization algorithm is proposed.

    在总结现有的矢量数据向栅格数据转换算法的基础上,提出一种面积误差最小约束下的优化算法。

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  • The adaptive parameter optimization algorithm is applied to dynamically search the parameters of FSVM(Fuzzy Support Vector Machine) to enhance the convergence speed.

    为提升算法的收敛速度,采用参数自适应优化算法动态搜索模糊支持向量机的模型参数。

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  • Expressing decision variables of the structure optimization problem in the form of vector, a 0-1 integer nonlinear programming model is presented.

    该结构优化问题的决策变量采用了向量表示方法,建立0-1整数非线性规划模型,给出了可行解存在性的判定方法。

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  • Particle swarm optimization- support vector machine classification has slightly better result than self-organizing neural networks, but the complexity of network was increased.

    粒子群优化支持向量机分类效果稍好,但是增加了网络的复杂度;

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  • A hybrid search method is proposed for the efficiency optimization of vector controlled induction motors.

    针对异步电机效率优化问题,提出了一种混合搜索方法。

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  • Through the research of cross-section shape control methods, scale vector is finally chosen to be applied as the control technique for shape optimization.

    通过对截面形状控制方法的研究,选择比例向量法对截面进行优化控制。

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  • Optimization of feature selection, we select area, perimeter, long axis, short axis, Euler number, geometric moments, and a total of 12 feature parameters as input vector.

    优化特征选择,选定面积、周长、长轴、短轴、欧拉数、几何矩等共12个特征参数作为神经网络输入向量进行分类试验。

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  • A slope stability evaluation method based on particle swarm optimization (PSO) and least square support vector machine (LSSVM) is proposed.

    提出了基于粒子群算法(PSO)和最小二乘支持向量机(LSSVM)的边坡稳定性评价方法。

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  • The invention discloses an optimization method and a device for verifying a vector.

    本发明公开了验证向量的优化方法及装置。

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  • The invention discloses an optimization method and a device for verifying a vector.

    本发明公开了验证向量的优化方法及装置。

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