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1)  Improved K-means Clustering
改进K-means聚类
1.
Application of Improved K-means Clustering Phylogenetic Profile in Gene Functional Annotation;
基于改进K-means聚类的系统发育谱方法在基因功能注释中的应用
2)  improved k-means clustering algorithms
改进型K-means聚类算法
3)  K-means clustering
K-means聚类
1.
More effective algorithm for K-means clustering;
求解K-means聚类更有效的算法
2.
Research on segmenting color regions in textile printing image based on K-means clustering;
基于K-means聚类的纺织品印花图像区域分割
3.
Collaborative filtering recommendation model based on effective dimension reduction and K-means clustering
一种结合有效降维和K-means聚类的协同过滤推荐模型
4)  K-Means cluster
K-Means聚类
1.
This paper adopted K-Means cluster to undertake spatio-temporal analysis of the number of tourists in Yancheng eco-tourism area for David s deer.
本文采用K-Means聚类法对盐城麋鹿生态旅游区游客数进行时空聚类,分别从省内和国内(省际)两个尺度上讨论了麋鹿生态旅游区游客变化的阶段性和市场划分,结果表明,1998~2005年间省内旅游流和国内(省际)旅游流从时间上可分为三个阶段,并较好地划分出了四种不同的客源地类型。
2.
Aiming at the high risk of customer loan contract violation in bank enterprise,combining a characteristic analysis model in economics with K-MEANS cluster algorithm in data mining,this paper carries on customer credit rating by using existing customer materials,thus realizing the high quality management of customer information,reducing the risk of bank loans.
针对银行业中客户贷款契约违约风险较高的问题,通过把经济学中的特征分析模型与数据挖掘中的K-MEANS聚类算法相结合,利用现有客户资料,对客户资信评级分类,从而实现对客户信息的高质量管理,降低银行对客户贷款的风险。
5)  improved K-means
改进K-means算法
6)  K-means clustering algorithm
K-means聚类算法
1.
Research on a method for building up a patent map based on k-means clustering algorithm
基于k-means聚类算法的专利地图制作方法研究
2.
In order to obtain better clustering results,after analyzing the advantages and disadvantages of hierarchical and k-means clustering algorithms,a new algorithm which combines the advantages of hierarchical and k-means clustering algorithms is proposed.
改进算法将分层聚类和k-means聚类算法的优点相结合,首先采用分层聚类,得到一个初始的聚类结果,然后应用k-means聚类算法继续聚类。
3.
The complexity of time and spatial is becoming the difficulty of K-Means clustering algorithm while it deals with the huge amounts of data sets.
K-Means聚类算法在面对海量数据时,时间和空间的复杂性已成为K-Means聚类算法的瓶颈。
补充资料:deacidification of oils and fats by physical means
分子式:
CAS号:

性质:在高真空条件下将油脂加热到适当温度使油脂中的游离脂肪酸挥发而脱除的方法。一般可采用降膜式蒸发器进行。残压应低于200Pa;加热应在不引起油脂分解的温度以下。挥发的脂肪酸通过冷凝回收。进料油脂要预先经过脱胶;主要是降低磷脂的含量使残余磷脂含量低于5mg/kg。此法适用含游离脂肪酸较高的油脂的初炼;可大幅度节约碱的消耗,降低皂脚所带走中性油的损失,并减少从皂脚中回收脂肪酸的工作量;因此有较高的经济性。

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