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embeddings相关的网络例句

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与 embeddings 相关的网络例句 [注:此内容来源于网络,仅供参考]

Secondly,the transformed query trees derived by the sequences of the basic transformation operations are used to perform exact embeddings into XML data tree,so as to transform the problem of approximate XML query into the problem of exact XML query for transformed query trees.Thirdly,XML data distribution statistics based similarity degree computing model and optimization algorithm for TopK problem are given.

XML文档具有灵活的表达能力,而这种灵活的表达能力使得不同组织和个人建立的XML文档,难以遵照一个统一的数据模式,即使内容完全相同的文档,不同的组织和个人也很难按照统一的标准来建立结构和标识内容完全相同的XML文档,从而造成了XML文档数据的多样性。

Based on the properties of associated surfaces for complete bipartite graphs,a new type of graph J with weak symmetry is constructed.At the same time,the minimum genus of it is derived.Finally,the number of genus embeddings of complete bipartite graphs is easily estimated.

然后基于完全二部图关联曲面的特点进行推广,构造了对称性比较弱的新图类J且得其最小亏格,最后对完全二部图不同最小亏格嵌入的数目作了估算。

RP is an architecture proposed in reference[1],which has uniform connectivity,small diameter and simple structure.Based on RP,the architecture of 10*k double-loop networks is designed.Algorithm DLN-RP about the embeddings of DLN into RP is proposed,and the values of expansion,load factor,dilation,congestion are given and proven to be optimal.

构造了10*k个节点的双环网结构,基于文献[3]提出的互连网络RP,提出了一种将双环网嵌入RP的算法DLN-RP,此算法得到的4个性能参数为拓展、负载、延伸、拥挤度分别为1,1,2,2,并证明了该结果为最优值。

The method is realized via the following steps: first to apply Isomap or LLE to get the embeddings of the original data set in the low dimensional space; then to obtain support vectors, which are the most significant and intrinsic data for the final classification result, by using support vector machine on these low dimensional embedding data; subsequently to get support vectors in the original high dimensional space based on the corresponding labels of the obtained low dimensional support vectors; finally to apply support vector machine again on these high dimensional support vectors to gain the final classification discriminant function.

数据挖掘是数据库知识发现中最重要的步骤之一,其目标是从获取的数据中高效准确地挖掘出我们所需要的信息。在实际应用中,数据往往呈现海量、高维、非线性等特性,这些特性给数据挖掘带来了很多问题,例如海量特性导致的计算效率低下问题、高维特性带来的维数灾难问题和非线性特性引起的线性模型失效问题等。幸运的是,实际中高维数据的属性之间往往存在一定的规律性和相关性,即实际数据经常存在着外在与内在两个维数。

In this project, we propose a novel 3D morphing technique that avoids creating a merged embedding that contains the faces, edges and vertices of two given embeddings. This novel 3D morphing technique dynamically adds or removes vertices to gradually transform the connectivity of 3D polyhedrons from a source model into a target model and simultaneously creates the intermediate shapes.

中文摘要在本专题研究计画中,我们提出一项新的三维物体变形技术,此变形技术所能处理的资料型态为two-manifold 之三维网格物体,此技术不需产生一个共有的高复杂度的网格物体或对原始物体进行重新网格化以产生相同连接关系,取而代之的是直接进行来源与目的物体之间几何与连接结构之转换,我们称此项新技术称为渐进式连接结构之转换(progressive connectivity transformation),此技术藉由动态增加或移除顶点的方式从来源物体到目的物体逐渐地进行连接结构转换同时使用线性位置内差来产生一序列中间物体。

In this project, we propose a novel 3D morphing technique that avoids creating a merged embedding that contains the faces, edges and vertices of two given embeddings. This novel 3D morphing technique dynamically adds or removes vertices to gradually transform the connectivity of 3D polyhedrons from a source model into a target model and simultaneously creates the intermediate shapes.

在本专题研究计画中,我们提出一项新的三维物体变形技术,此变形技术所能处理的资料型态为two-manifold 之三维网格物体,此技术不需产生一个共有的高复杂度的网格物体或对原始物体进行重新网格化以产生相同连接关系,取而代之的是直接进行来源与目的物体之间几何与连接结构之转换,我们称此项新技术称为渐进式连接结构之转换(progressive connectivity transformation),此技术藉由动态增加或移除顶点的方式从来源物体到目的物体逐渐地进行连接结构转换同时使用线性位置内差来产生一序列中间物体。

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推荐网络例句

I didn't watch TV last night, because it .

昨晚我没有看电视,因为电视机坏了。

Since this year, in a lot of villages of Beijing, TV of elevator liquid crystal was removed.

今年以来,在北京的很多小区里,电梯液晶电视被撤了下来。

I'm running my simile to an extreme.

我比喻得过头了。