向量

This paper describes a new method for constructing a rough neural network. In this network, rough neurons lie in the hidden-layer, and they consist of three parts which generated by two hyperplanes that partition the universe.

本文根据支持向量机可以解决小样本学习问题的优势，再结合粗集理论对不确定性问题分析的特点，提出一种支持向量机的粗糙神经网络的构造方法。

The traditional classification methods only use one single classifier, which may lead to onesidedness, low accuracy, and that the samples nearby the Support Vector Machine hyperplanes are more easily misclassified. To solve these problems, the multifeature fusion method based on SVM and KNearest Neighbor classifiers was presented in this paper.

针对传统分类方法只采用一种分类器而存在的片面性，分类精度不高，以及支持向量机分类超平面附近点易错分的问题，提出了基于支持向量机和k近邻的多特征融合方法。

Bases on the XML Key, the algorithm firstly dealt with XML structure to vector matrix, then used project frequent pattern tree to optimize the XML structure through dissociating, uniting, updating and canceling to satisfy the conciseness of the XML structure and query multiversity.

该算法以XML键为基础，利用向量矩阵处理方法、投影频繁模式树实现XML结构的分裂、合并、更改与取消等操作，同时讨论XML键向量矩阵频繁项集的划分规则及相应启发式策略与支持度阈值。

For the regular curves, we find two Killing fields for the purpose of integrating the structural equations of the p-elastic curves and express the p-elastica by quadratures in a system of cylind...

对于正则曲线的情形，我们发现了两个用于求解p-弹性曲线的结构方程的Killing向量场并用积分将p-弹性曲线在一个柱面坐标系中表示出来，而对仿射星形曲线的情形，我们用积分方法解出了欧拉-拉格朗日方程，利用Killing向量场及线性李代数s1(2，R)、s1(3，R)和s1(4，R)的分类将高阶结构方程降为一阶线性方程，因此我们用积分完全解出了中心仿射p-弹性曲线。

For the regular curves, we find two Killing fields for the purpose of integrating the structural equations of the p-elastic curves and express the p-elastica by quadratures in a system of cy...

对于正则曲线的情形，我们发现了两个用于求解p-弹性曲线的结构方程的Killing向量场并用积分将p-弹性曲线在一个柱面坐标系中表示出来，而对仿射星形曲线的情形，我们用积分方法解出了欧拉-拉格朗日方程，利用Killing向量场及线性李代数s1(2，R)、s1(3，R)和s1(4，R)的分类将高阶结构方程降为一阶线性方程，因此我们用积分完全解出了中心仿射p-弹性曲线。

For the regular curves, we find two Killing fields for the purpose of integrating the structural equations of the p-elastic curves and express the p-elastica by quadratures in a syste...

对于正则曲线的情形，我们发现了两个用于求解p-弹性曲线的结构方程的Killing向量场并用积分将p-弹性曲线在一个柱面坐标系中表示出来，而对仿射星形曲线的情形，我们用积分方法解出了欧拉-拉格朗日方程，利用Killing向量场及线性李代数s1(2，R)、s1(3，R)和s1(4，R)的分类将高阶结构方程降为一阶线性方程，因此我们用积分完全解出了中心仿射p-弹性曲线。

For example, a cube is made up of six quadrilaterals where each vertex is shared by three polygons, but a different normal should be used for each of the three instances of each vertex, but a sphere is made up of many polygons where all vertices have common normals.

例如，一个立方体是由六个四边形组成，而每一个顶点被三个多边形共用，但是每一个顶点的三个实例应该使用不同的法向量，而由许多多边形组成的球，其所有顶点就有同样的法向量。

Since the commanded guidance acceleration is achieved by thrust vector control system in midcourse phase, we design two loops flight control system to stabilize the attitude and achieve the guidance command by TVC system.

由於中途导引阶段的导引加速度由推力向量控制(Thrust Vector Control，TVC)系统来达成，因此设计双回路飞行控制系统来稳定姿态并且使推力向量达到导引律的需求。

There are four parts presented in this paper. In the first part, the B.F ironmaking process, B.F Expert System and the methods to predict the silicon content in molten iron are introduced. In the second part, the control parameters and state parameters of B.F ironmaking process are analyzed. In the third part, the Statistical Learning Theory and Support Vector Machine are introduced.

论文主要包括以下四个方面的内容：高炉炼铁、高炉专家系统和炉温预测的概述；高炉冶炼过程状态参数和控制参数的分析；统计学习理论和支持向量机方法；基于支持向量机的铁水硅含量数值预报模型和铁水硅含量多类别分类模型。

The number of support, vectors is decreased by 28%. Then, the structure of the Riemannian geometry is introduced in the input space, and using the Riemannian geometric modifies the kernel function of the classifier and gets less improved support vectors at the second training.

在第一次训练后产生的支持向量的基础上，将黎曼几何结构引入到输入空间，利用黎曼几何结构将分类器中的核函数进行修改，在第二次训练中再次减少了支持向量数目。

The labia have now been sutured together almost completely.The drains and the Foley catheter come out at the top.

此刻阴唇已经几乎完全的缝在一起了，排除多余淤血体液的管子和Foley导管从顶端冒出来。

To get the business done, I suggest we split the difference in price.

为了做成这笔生意，我建议我们在价格上大家各让一半。