动态聚类分析,dynamic cluster analysis
1)dynamic cluster analysis动态聚类分析
1.According to the date of water quality collected from Taihu Lake in 1987—1988, seventeen indexes in three pollution types of organic matter, hygienic index, nutrients, toxic and harmful materials were evaluated by means of a systematicdynamic cluster analysis.根据1987—1988年太湖实测水质数据,利用系统动态聚类分析方法,将17个指标按营养盐、有机质、有毒有害物质三种污染类型进行综合评估,获得了太湖水域各类污染指标空间分布态势及差异特点,揭示了太湖现存的三种污染模式及地域分布状况,为进一步治理和改善太湖水质提供依据。
2.A practical class template ofdynamic cluster analysis that is developed in object oriented programming language is introduced.介绍一种用Ｃ＋ ＋ 面向对象编程语言开发的动态聚类分析类模板，它适用于ＤＯＳ和ＷＩＮＤＯＷＳ运行环境，只需较少的信息和编程，便可完成整型、单精度实型、双精度实型的向量矩阵、动态聚类分析的基本运算。
英文短句/例句
1.Model of Air Attack Formation Estimation Based on Dynamic Clustering Analysis;基于动态聚类分析的空袭编队判断模型
2.Dynamic Clustering Analysis of Return Series of Industrial Indexes in Chinese Stock Market;中国股票市场行业收益率序列动态聚类分析
3.An Evaluation of the Slope Stability in the East of Gansu Province甘肃东部地区斜坡稳定性动态聚类分析评价
4.Approach to radar signal radio frequency recognition based on dynamic clustering基于动态聚类分析的雷达载频模式识别
5.The Method for Lithology Classification in Geophysical Well Logging Based on the K-means Dynamic Clustering Analysis基于K均值动态聚类分析的地球物理测井岩性分类方法
6.Study on Method of Teaching Quality Evaluation Based on Fuzzy Cluster;基于模糊动态聚类分析的教学质量评估方法研究
7.Fuzzy Cluster Analysis of Population Dynamics of Field Larva of the Mosquito Aedes Albopictus白纹伊蚊幼虫自然种群动态的模糊聚类分析
8.A fusion clustering algorithm based on dynamic data windows and its applications in fault detection基于动态数据窗口的融合聚类分析与故障检测
9.Face recognition based on linear projection analysis and FCM dynamic clustering基于线性投影分析和FCM动态聚类的人脸识别
10.APPLICATION OF FUZZY CLUSTRING ANALYSIS TO STUDY ON THE EPIDEMIC DYNAMICS OF RICE SHEATH BLIGHT模糊聚类分析在稻纹枯病流行动态研究中的应用
11.APPLICATION OF FUZZY CLUSTER ANALYSIS IN THE STUDIES ON EPIDEMIC DYN AMIC OF MARSSONINA MALI模糊聚类分析在苹果褐斑病流行动态研究中的应用
12.Study of the Population Dynamics of the Parasitic Fleas on Citellus undulatus Appling Fuzzy Cluster Analysis应用模糊聚类分析考察长尾黄鼠体外寄生蚤的种群动态
13.Fuzzy Cluster Analysis on Dynamic of Mixed Spider Population in Alfalfa Grassland苜蓿草地地表蜘蛛混合种群动态的模糊聚类分析
14.Fuzzy cluster analysis of the dynamics of egg density and egg parasitism of Empoasca vitis (Gthe)假眼小绿叶蝉卵密度及其寄生率消长动态的模糊聚类分析
15.Assembling Analysis of Forest Eco-Economic System in Hainan Island;海南岛森林生态经济系统的聚类分析
16.Clustering Analysis in Condition Assessment Factor Classification of Circuit Breaker;模糊聚类分析用于断路器状态评估因素分类
17.Principal component analysis and cluster analysis of morphological traits in eggplant茄子形态学性状主成分分析及聚类分析
18.A Projection Pursuit Classification Model Based on K-Means Dynamic Cluster基于K-Means动态聚类的投影寻踪分类模型
相关短句/例句
auto-clustering analysis自动聚类分析
3)cluster analysis聚类分析
1.Application of Cluster Analysis in the Judgment of the Aluminum Electrolyzer"s Status;聚类分析在铝电解槽况判断中的应用
2.Water quality andcluster analysis of Huaihe River Basin in ;淮河流域水质状况和聚类分析
3.Failure analysis of drill stem based on support vector machine andcluster analysis theory;基于支持向量机和聚类分析理论的钻具失效分析方法
4)clustering analysis聚类分析
1.Fuzzyclustering analysis of body type in 2D non-contacted body measurement system;二维非接触人体测量中体型的模糊聚类分析
2.Study on ranking standard of enterprise occupational injury risk based onclustering analysis of SPSS;基于SPSS聚类分析的企业职业伤害风险分级标准研究
3.Study on eco-environment quality assessment based on factor andclustering analysis;基于因子分析和聚类分析的生态环境质量评价
5)Hierarchical cluster analysis聚类分析
1.HPLC fingerprint of Radix et Rhizoma Gentianae and its hierarchical cluster analysis;龙胆药材的高效液相指纹图谱及聚类分析
2.HPLC fingerprint of Eclipta prostrata L.and its hierarchical cluster analysis;墨旱莲药材的高效液相指纹图谱及聚类分析
3.Hierarchical Cluster Analysis on HPLC Fingerprint of Folium Mori from Different Breeds;不同品种桑叶高效液相指纹图谱的聚类分析
6)Clustering[英]["kl?st?][美]["kl?st?]聚类分析
1.Application of clustering in Dalian marine environment evaluation;聚类分析功能在大连港水域环境质量评价中的应用
2.An algorithm for clustering based on projected cluster;一种基于映射簇的聚类分析算法
3.Classification approach for shape grading of strawberry based on clustering;基于多元聚类分析的草莓形状分类算法
延伸阅读
动态模糊聚类法分子式：CAS号：性质：又称动态模糊聚类法。选定一批聚类中心，其指标能反映该类的特征，将样本向最近的聚类中心聚类。再根据分类结果确定新的聚类中心，其各项指标为该类中所有样本的相应指标的平均值。然后计算前后两聚类中心的差异，如差异大于某一阈值，说明分类不合理，需修改分类，即以新的聚类中心代替旧的聚类中心，直到前后两聚类中心的差异小于某一阈值，认为分类合理，从而终止分类过程。
