主成分得分 meaning in Chinese
principal component score
Examples
- In this paper , the near - infrared spectral measurement and principal component analysis ( pca ) of simulated spilled petroleum samples are made , the princpal component scores are taken as the cluster characteristic variables for making fuzzy clustering , the near infrared spectrometry and pca together with fuzzy clustering method are then used for rapid recognition of simulated spilled oils , and the sample clustering and recognition patterns are established
摘要对模拟溢油的石油类样品进行近红外光谱检测并进行了主成分分析，以主成分得分作为聚类的特征变量进行模糊聚类，采用近红外光谱测量结合主成分分析和模糊聚类法快速识别模拟溢油种类，并建立了样品聚类与识别模型。 - Firstly , the weighted value of every idiographic indicator in this system was established by analytical hierarchy process , and weighted arithmetic average was used to determine the analysis results of the indicators " values of six aspects . then the principal component analysis were used to calculate the principal component values of twenty enterprises that can be divided into five developmental types according to their principal component values . the five types were as follows : 1 ) highly developmental level and highly potential type ; 2 ) highly developmental level and lower potential type ; 3 ) highly developmental level and no potential type ; 4 ) low developmental level and highly potential type ; 5 ) low developmental level and no potential type
首先，通过层次分析法确定指标体系中16项具体指标的权重，并采用加权算术平均法确定6项评价指标的评价结果；然后，结合gwbasic和spss软件对六个方面指标进行主成分分析，得出各企业的主成分得分；最后，通过聚类的方法将调查的20家涉农企业分为五种不同的发展类型： 1 )高发展水平、高潜力型企业； 2 )高发展水平、低潜力型企业； 3 )高发展水平、无潜力型企业： 4 )低发展水平、高潜力型企业；和5 )低发展水平、无潜力型企业。