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1.Under the Euclidean measure, the analytical solutions to the above problem are obtained by employing the Riemann Liouville fractional calculus theory.
在欧氏测度下 ,应用R L分数阶微积分算子理论给出了上述问题的精确解 .收藏指正
2.The thesis puts complex variable into C2-space and studies it as a measure. After comparing and contrasting it with Euclidean measure, it discusses the relevant properties of real measure of general entire function and those of the harmonic function, as well as the suprimum of entire function so as to lay foundation for the growth research of the entire function.
将复变量整函数引入C2中,作为一个范数来研究,并比较这一类范数与Euclidean范数的异同,初步探讨了一般整函数表示的实范数、调和整函数所表示的实范数的相关性质,以及整函数的确界性质,以作为研究整函数的增长性的基础.收藏指正
3.The technique supports Euclidean distance measure and L-shift Euclidean distance measure.
这种方法支持欧几理德距离标准和 L -平移欧几理德距离标准 .收藏指正
4.E isincorporated into the exponentiation part of the Gibbs distribution while DS* is compared to four similarity measures: L_1, L_2 (Euclidean distance), the similarity measure E in addition toGibbs distributions integrating E.
其中我们将E合成到了吉布斯分布的幂部分，并将DS~*与四种相似度量方法分别作了比较。 这四种相似度量方法分别为：L_1，L_2(欧氏距离)，E，E+吉布斯分布。收藏指正
5.Euclidean distance is taken as similarity measure and the group average method is used as clustering algrithm
分类是用欧氏距离作为相似性测度,聚类算法采用类平均距离法,得到一系统聚类图。收藏指正
6.The Euclidean distance is usually chosen as the similarity measure in the conventional K-means clustering algorithm, which usually relates to all attributes.
传统的K-均值算法选择的相似性度量通常是欧几里德距离的倒数，这种距离通常涉及所有的特征。收藏指正
7.The Euclidean distance is usually chosen as the similarity measure in the conventional K-NN algorithm, which usually relates to all attributes.
传统的K-近邻算法选择的相似性度量通常是欧几里德距离的倒数,这种距离通常涉及所有的特征。收藏指正
8.It is shown that the monotone function acting between Euclidean Spaces R n and R m is continuous almost everywhere with respect to the Lebegue measure on R n.
证明了一个定义于Rn 至Rm 欧几里德空间的单调函数在Rn 的Lebegue测定意义上是几乎处处连续的收藏指正
9.The author analyzed the following aspects by SPSS software and the measure of Euclidean Distance: (1) analyzed the relationship between grasshopper species and geographical distribution and divided 9 forestrybelt into 3 main habitat model: low mountain conifer and broadleaf integrated forestry belt; low mountain Chanbai conifer forestry belt and middle-high conifer-Betula ermam/-tundra belt;
在长白山地区蝗虫生态分布特点的研究中，主要应用SPSS软件包、采用Euclidean distance测度法对以下两方面内容进行了分析：(1)对长白山地区蝗虫地理分布关系进行了分析，将长白山9个林带划分为三大生境型：低山针阔叶混交林带、低山长白松林带和中高山针叶—岳桦—苔原复合体；收藏指正
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