This paper analyzes the problems in data input of digital map publish especially in vector data input, and indicates the importance of multi-source vector data use.
文中分析了当前数字地图出版中数据输入尤其在矢量数据输入方面存在的诸多问题，指出了多源矢量数据利用的重要性。
Subsequently those preprocessing data are the input of SVM (support vector machine) algorithm, which is used for ball bearing fault detection.
将预处理后数据作为SVM(支持向量机)算法的输入，通过SVM算法来检测轴承故障。
Therefore, through structural modal analysis with different damage degree using ANSYS, get natural frequencies and mode shape data as neural network input vector after unitary.
因此，通过有限元软件ANSYS对具有各种损伤程度的结构进行模态分析，得到固有频率和模态分量的数据，经过归一化处理后作为神经网络的输入向量。
Kernel Methods are concerned with mapping input data into a higher dimensional vector space where some classification or regression problems are easier to model.
核函数方法关心的是如何把输入数据映射到一个高维度的矢量空间，在这个空间中，某些分类或者回归问题可以较容易地解决。
Kernel Methods are concerned with mapping input data into a higher dimensional vector space where some classification or regression problems are easier to model.
核函数方法关心的是怎样把输入数据映射到一个高维度的矢量空间，在这个空间中，某些分类或者回归问题可以较容易地解决。
Its capabilities include: data input, geographical analysis (raster, vector and site), manipulate multi-spectral images and map display.
其功能包括：数据输入、地理分析(栅格、矢量、点)、多光谱图像处理、地图显示。
With the data of characteristic singular values of sub-images, the Local Singular Value Vector of the whole image are combined, and are used as the input of the classifier.
子图像的特征奇异值组成整个图像的局部奇异值向量，作为分类器的输入。
Through SVM algorithm, solving the building problem of input sample feature vector (weak information sample) in the process of extracting mineralizing information from RS data.
解决了应用SVM识别算法对遥感矿化信息提取过程中输入样本特征向量（微弱信息样本）的构造问题。
The whole design has succeeded in the test of large data input, operation in each instruction, border condition and every random data vector. The code coverage has reached the percentage of 100%.
整个设计通过了海量数据输入测试，并对各种指令的操作数、边界情况和各种随机数据组合进行了充分模拟，代码覆盖率为100%。
The whole design has succeeded in the test of large data input, operation in each instruction, border condition and every random data vector. The code coverage has reached the percentage of 100%.
整个设计通过了海量数据输入测试，并对各种指令的操作数、边界情况和各种随机数据组合进行了充分模拟，代码覆盖率为100%。
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