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A support vector regression model based on batch to batch optimal control strategy was proposed.

针对间歇过程的优化问题,提出了一种基于支持向量回归模型的批次到批次的优化控制策略。

This algorithm updates probability vector by variety of population diversity and evolutionary state of every gene.

该算法通过种群多样性的变化和每个基因座自身的进化状态来控制概率向量的更新。

First,the rational optimal objective function for acoustic field pattern is put forward. Then, two optimal algorithms for global optimization are proposed.

在对空间声场提出合理的优化目标函数后,提出了两种优化算法进行全局寻优:一种是遗传算法构造的声场模式控制算法;另一种是特征向量算法。

Secondly, we propose a kind of"regressor vector-based"nonlinear adaptive control scheme.

然后,提出了一种"基于回归向量"的非线性自适应控制方法。

In our"regressor vector-based"design, we come over these drawbacks, and construct a novel model reference adaptive nonlinear tracking controller for more general systems.

而"基于回归向量"的设计突破了上述局限,可以对更一般的控制对象建构模型参考自适应跟踪控制器。

Meanwhile, we have gotten stability for the subdifferential of cone efficient point sets and cone weakly efficient point sets of multiobjective programming with respect to perturbation of cone respectively.

对于局部凸拓扑向量空间的多目标规划问题,本文研究并得到当确定空间序的控制锥受扰动,它们的锥有效点集和锥弱有效点集分别在锥次微分和锥弱次微分意义下的稳定性结果。

Firstly, kinetic energy and potential energy expressions are obtained by a series of derivation, considering the extrinsic momentum. In the symplectic system, control equations of longitude and transverse coupling vibrations of rotating elastic structures, or Hamilton canonical equations are described. So the solution of the problem is boiled down to the eigenvalues and eigensolutions in the symplectic space.

首先,从能量的观点出发,通过一系列的理论推导,给出旋转结构的动能和势能表达式,并考虑外动量的影响,从而得到在辛体系中描述旋转结构纵向和横向耦合振动的控制方程,即哈密顿正则方程,于是将问题归结为辛几何空间的本征值和本征向量问题。

Different from traditional system protection models, such as access control matrix model, this theory describes the operations in system by functions of random variable vectors, build an analysis model of trusted system with three axioms, and analyze the information flow in the system by tracing the operation sequence of the system.

与访问控制矩阵模型等传统的保护系统模型不同,这一理论用随机变量向量的函数来描述系统操作,基于三条公设建立了可信系统的分析模型,并通过对系统操作序列的跟踪来分析系统中的信息流。

First, a non-negative tensor factorization algorithm is improved by imposing sparseness constraints on it. Secondly, the bispectral images of mechanical signals are obtained and stacked to form a third-order tensor. Thirdly, the improved algorithm is used to extract features, which are represented by a series of basis images from this tensor. Finally, coefficients indicating these basis images' weights in constituting original bispectral images are calculated for fault classification.

首先,改进已有的非负张量分解算法,加入稀疏度控制策略;其次,将机械振动信号的双谱图像堆叠为一个三阶张量;然后利用改进后的分解算法对该张量进行二次故障特征提取,得到代表局部特征的"基图像";最后,通过计算得出基图像在构成原双谱图像中所占的权重,并将得到的权重向量用于故障分类。

We use a size changeable adjacent field to describe the topological structure of 3D unorganized points in our algorithm. It can offer essential dynamic information for tessellation and points normal.

算法采用可以控制大小的邻域作为空间散乱数据点的拓扑关系的几何描述,为网格划分和点的法向量的几何描述提供了必要的动态几何信息。

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