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This approach not only inherits the advantages of absolute density based algorithms which can discover arbitrary shape clusters and are insensitive to noises , but also efficiently solves the following common problems: clustering results are very sensitive to the user-deflned parameters, reasonable parameters are hard to be determined, and high density clusters are contained fully in coterminous low density clusters. With this approach, incremental clustering can also be supported effectively by defining the affected sets and seed sets of the updating objects in this approach.

聚类算法的有效性问题主要表现在三个方面:其一,聚类算法大多要求用户输入一定的参数,例如希望产生的簇的数目,而这些参数通常难以确定,特别是针对高维空间中稀疏分布的实际应用数据集,用户几乎无法给出合适的算法参数,因此非专业用户需要与数据分析专家密切配合才能保证获得理想的聚类结果,导致算法的使用极为不便;其二,聚类结果对于输入的参数值过于敏感J,往往参数值的一些轻微变化却产生聚类结果的很大差异;其三,对于高维的实际应用数据集,其数据分布往往是稀疏的、杂乱的,很难为算法选择全局的参数进行准确的聚类分析,使得聚类的质量难以保证。

Our results reveal that with the same number of cobalt atoms and the same cobalt-substrate interation stength, the melting points and pre-melting intervals of the two kinds of supported Co clusters are all in reasonable agreement with each other. With increasing the depth of supported potential, the melting points increase for the supported cluster. Similar to the case of free clusters, the linear relation between the melting point and the inverse of cluster's size cube root is also found for the two kinds of supported clusters.

结果表明:对于给定原子数目的支撑Co团簇,在衬底势强度相同时,两种衬底势下对支撑团簇熔点及预熔化区间给出了一致的描述;随衬底势强度增加,支撑团簇熔点升高,且两种衬底势所描述的支撑Co团簇也类同于自由Co团簇都表现出较好的熔点与尺寸依赖的线性关系。

The results show that the ground state structures of CB(superscript -)(n=1~6) clusters are linear as C clusters due to their isoelectrons. For CB (n=1~6) clusters, the ground state structure of C2B is asymmetric triangle and C6B is C(subscript 2v) symmetry planar monocycle, while the other clusters are linear.

结果表明CB(n=1~6)团簇的基态构型均为线形,这与等电子的C簇合物的结构是一致的;CB(n=1~6)团簇的基态构型中,除C2B为不对称的三角形,C6B为具有C(下标 2v)对称性的环状结构外,其余均为线形结构。

With the organization characteristics and its competitiveness of industrial clusters as middle network organization, the dissertation constructs a non-symmetry diamond model of FDI-driving industrial clusters by expanding Porter's diamond model, therefore spreads the securable advantage of clusters from local network to global network.

实证则以硅谷集群为例研究了跨国公司总部集群与产业集群的组织创新,以及以台商在中国大陆的投资研究了跨国公司分厂经济与产业集群的组织创新,证实了理论研究的结果。

It was found:(1) the stability of the clusters increased with the bond number in the clusters;(2) the clusters with three dimensional geometry are more stable than ones with two decisional geometry;(3) the ionic potential of the clusters in gas phase and on the surface of the silver bromide grains are all positive, and the electron affinity are all negative.

结果表明;气相中团簇的稳定性随团簇中键数的增加而升高,三维构型的稳定性大于二维构型的稳定性;气相中Ag〓团簇的电离能都大于零,电子亲和势都小于零;溴化银颗粒表面的Ag〓团簇的电离势也是大于零,电子亲和势也是小于零。

The third chapter aims to discuss the self-organization essence, self-organization growth mechanism, the pattern of self-organization evolving growth.The fourth chapter aims to discuss particularly the correlative mechanism between clusters dynamic core capacity and clusters sustainable growth, and the obtaining of cluster sustainable competitive advantage basede on dynamic core capacity and the fostering and newing of cluster dynamic core capacity based on discussing the rigid competitive advantage. The fifth chapter aims to explain the effecting mechanism of government influencing cluster self-organization-evolvement and the fostering and upgrading of cluster dynamic capacity based on the theory gist of government surpports .The sixth chapter aims to analyse the High-tech industrial clusters of Silicon Valley in American and Low piezoelectricity cluster of Liu shi in zhengjiang province and explains to how self-organization , dynamic core capacity and government surpports effect industrial clusters sustainable gowth.The dissertation's main innovation lies in the following :mechanism model of cluster sustainable growth is constructed under dynamic environment based on self-organization theory and dynamic core capacity theory .

本文共分6章,第1章主要阐述本论文的研究背景、研究问题和研究意义,综述相关的国内外文献,并提出本论文的研究逻辑思路、研究方法和主要内容;第2章在对产业集群本质再认识和集群持续成长内涵分析的基础上,从自组织理论和动态核心能力理论视角,构建了动态环境下集群持续成长机制的概念模型;第3章主要探讨了集群持续成长的自组织本质、自组织成长机理和自组织演化成长模式;第4章在分析集群竞争优势刚性的基础上,提出集群动态核心能力的概念,分析了集群动态核心能力的构成要素及其对集群持续成长的作用机制,探讨了集群动态核心能力的演进与产业集群持续成长的关联机理,并进一步探讨基于集群动态核心能力集群持续竞争优势的获取问题,最后是关于集群动态核心能力的培育与更新的探讨;第5章在论述政府对集群支持的理论依据的基础上,分别探讨了政府对集群自组织演进和对集群动态核心能力的培育和提升的作用机制;第6章实例研究,论文选取了美国硅谷高科技产业集群和浙江柳市低压电器产业集群进行实例分析,研究了自组织、动态核心能力和政府支持三大机制在集群持续成长过程中的作用。

The calculated results show that azido in azides has linear structure , the most optimized CaN6 has linear structure , and the most optimized (CaN6)n (n=2~5) clusters have chain structure of perpendicularity of approximate diamond composed by two azido with two Ca atoms . The middle N atoms of azido show positive, the N atoms at both ends of azido show negative, and the N atoms effected with Ca atoms directly show more negative . There is strong ionic bond between the Ca and N atoms. The IR spectra of the most optimized (CaN6)n (n=1~5) clusters have four vibrational sections , the whole strongest vibrational peak lies in 2195~2280cm-1,and the vibrational mode is anti-symmetric stretching vibration of N-N bonds in azido . Stability analysis show that (CaN6)3 and (CaN6)5 clusters are more stable than other clusters .

结果表明,叠氮化合物中叠氮基以直线型存在,CaN6团簇的最稳定结构为线型结构,(CaN6)n(n=2~5)团簇首先由两个叠氮基与两个Ca原子构成一个近似菱形,再由菱形相互垂直形成链状最稳定结构;叠氮基中间的N原子显示正电性,两端的N原子显示负电性,且与Ca直接作用的N原子负电性更强,金属Ca原子和N原子之间形成很强的离子键;(CaN6)n(n=1~5)团簇最稳定结构的IR光谱分为4个部分,其最强振动峰均位于2195~2280cm-1,振动模式为叠氮基中N-N键的反对称伸缩振动;稳定性分析显示,(CaN6)3和(CaN6)5团簇相对于其他团簇较为稳定。

Harmonic frequencies and infrared spectra intensity for these clusters are given in order to aid in the characterization of the ground states. The results show that Si2CmN(m=2-10) clusters form linear structure, which are doublet states. The Si atoms favor to bond at ends of C and N linear chain. The ground state energies of clusters are nearly in proportion to increased m. The stability of Si2CmN(m=2-10) clusters with even m are greater than that with odd m.

结果表明,m=2-10的团簇为线性结构,随着m的增大,团簇的自旋多重度均为2,Si原子在C与N原子形成的线性链端部成键,团簇的基态能量近似线性增大。m为偶数的Si2CmN团簇比m为奇数的更为稳定。

The gas-to-powder conversion is carried out following the route: DMS pyrolyzes and forms product molecule and molecular clusters, the product molecular clusters that grow to and above the critical size by random collisions with molecules and other clusters become elementary particles, the elementary particles grow further by collisions and fusion with molecules, clusters and other elementary particles to form resulted SiC particle.

论文采用TEM、HREM、XRD、IR、NMR、中子衍射、Raman光谱和定量化学分析、光透沉降粒度分析等手段,对制备得到的纳米SiC粉体进行了系统表征研究,并研究了SiC纳米粉体的成核、生长、晶化过程和机制,指出化学气相反应法制备SiC纳米粉体的过程是一个均匀成核→核子生长形成初始颗粒→初始颗粒熔融碰撞→产物粉体的过程。

An automatic algorithm was used in the analysis to identify clusters of groupings of patients. We used the classical unsupervised clustering method called the Iterative Self-organizing analysis technique of DATA analysis originally introduced by Ball and Hall.25 The technique allows the splitting and merging of clusters while trying to find the "best" configuration. It therefore, requires very little a priori knowledge about the data and predefining the possible number of clusters or groups is not required. The range of possible minimum and maximum number of clusters within which the algorithm can search for an optimal configuration was determined by a procedure called the chainmap which reorders the multidimensional data in the form of a 2D distance map.26 A patient vector is randomly selected and its nearest neighbor is identified as that with the shortest distance between the 2 patients' vectors.

使用自动算法来分析鉴别患者组的聚类,我们使用经典的最初由Ball和Hall提出的的非监控聚类方法,该技术允许在寻找&最佳&形态使对聚类进行拆分和组合,他不需要对数据专门的知识和对聚类或群的可能数量进行预设,在聚类可能的最大和最小范围内,算法可以通过一个叫Chainmap的程序寻找最理想的形态,该程序记录了来自2D距离图的多维数据。

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