主成分

zhǔ chénɡ fèn
  • principal component;major constituent
主成分主成分
  1. X荧光光谱法测定镍锌铁氧体中的主成分

    Determination of the Main Components in Ni-Zn Ferrite with X-ray Fluorescence Spectrometry

  2. GM(1,N)模型的病态矩阵的产生及主成分估计改进法

    Creating ill-conditioned matrix in GM ( 1 , N ) and improve method by principal component

  3. 特别指出,当变量X多重相关性突出时,该文方法显著地优于主成分分析方法。

    The method is markedly superior to of principal component analysis especially when X has serious multi-correlation .

  4. 微机环境下TM图象主成分变换及其信息特征分析

    Microcomputer based on PCA transformation of TM lmages and its information feature analysis

  5. 应用主成分分解(PCA)法的图像融合技术

    PCA method used in image fusion

  6. 主成分分析(PCA)分解法被广泛地应用于特征抽取的过程。

    A popular decomposition called principal component analysis ( PCA ) is widely used for feature extraction .

  7. GC-MS及主成分分析法用于咖啡香精的指纹图谱分析和微差样品的识别

    Fingerprint analysis of coffee flavor with GC-MS and principal component analysis and differentiation of little difference samples

  8. 为充分利用卷烟企业卷烟烟气常规检测数据,采用主成分分析、Z分数标准化、方差分析和多重比较以及模糊相近优先比等相结合的统计方法对卷烟烟气常规检测数据进行了分析。

    In order to make full use of the routine test data of cigarette smoke , the data was analyzed with various statistical methods .

  9. 首先通过主成分分析(PCA)结合多类判别分析建立了润滑油品牌鉴别模型。

    Firstly , principal component analysis ( PCA ) and multiclass discrimination analysis were combined to establish lubricant oild brand discrimination model .

  10. MEA信号锋电位的主成分分类

    Principle Component Sorting of MEA Signal Spike

  11. 3个品种的M5群体的2.5%跨长均为第一主成分的主要因子。

    2.5 % span length was the main factor in the first principal component .

  12. 用主成分分析法选取了最能代表西湖水质状况的7号点(湖心)作为研究对象,并用该方法筛选了部分水质参数,作为BP网络的输入变量。

    Selecting spot 7 which can most represent the water quality status of it as study object and filtrating the water quality parameters as the inputs for network by principal component analysis .

  13. 利用主成分分析法,得出泰安市耕地减少的四大驱动因子:农民人均住房面积、第一产业GDP、非农业人口和公路里程。

    The results showed that peasantry average house area , the first industry GDP , nonagricultural population and highway mileage are the four main factors of reducing cultivated land in Tai'an .

  14. 采用条件Logistic回归模型进行单因素分析,对单因素分析中有意义的预选变量进行共线性诊断后,进行主成分分析和因子分析,然后进行多因素分析。

    Conditional logistic regression , principal component analysis , factor analysis and generalized relative risk model were used to analyse the risk factors and the potential interactions between some risk factors .

  15. 基于主成分分析法的高校EHR系统

    University EHR System Based on Main Component Analysis

  16. 文中给出了基于Lyapunov指数谱的主成分聚类分析方法。

    At the same time , method of principle component cluster analysis based on Lyapunov exponent spectrum in this paper combines methods of statistics and nonlinear dynamical methods together .

  17. 通过对PCA中主成分的特征向量分析,以及对原始各波段的负荷因子分析可知,PCA变换处理在澜沧江流域土地覆盖遥感监测分类实施中,对波段选取具有一定的指导作用;

    Based on the analysis of feature vector and original bands loading on the main principal components , we known that PCA is of some affects about feature selection .

  18. 有监督的主成分回归和偏Cox回归方法将降维方法与Cox比例风险模型相结合,可以解决高维生物信息数据的生存预测问题。

    Supervised principal components analysis and Partial least squares Cox regression methods solve these problem by combine the Cox proportional hazards model with technique of dimension reduction .

  19. 在上述基础上,应用SPSS数学统计中的主成分分析法,对上海新市镇的发展水平进行了测评和分析,将新市镇发展水平分为三个等级。

    Based on the above-mentioned research , the present paper evaluates and analyzes the development of Shanghai new towns by applying the principal component analysis in SPSS mathematical statistics .

  20. 磨粒颜色与磨粒组成成分有很大的关联,本文使用主成分分析法在HSI色度空间上判断磨粒颜色,通过磨粒颜色分布确定磨粒组成成分。

    The primary component analysis was applied to the wear particle HSI color parameters to judge the composition of the wear debris .

  21. 结果:运用主成分分析得到TMP结构的三个因素(工作支持、工作反馈和心理互动);

    Using the SPSS statistical analysis , the results showed that three components of TMP ( job support , job feedback and psychological interaction ) .

  22. 研究了测量平差Gauss-Markov模型中岭-主成分组合估计与LS估计的比较与选择问题。

    The problem of selection between combining ridge and principal component ( CRPC ) estimator and LS estimator in Gauss-Markov model is studied .

  23. 针对上述问题,提出了信息增益(IG)与主成分分析(PCA)相结合的特征选择方法。

    Aiming at the preceding problem , this paper puts forward a feature selection method using Information Gain ( IG ) and Principle Component ( Analysis )( PCA ) .

  24. 对主成分因子进一步分析表明,养分主成分中速效氮起主要作用,酸碱特性主成分中以pH值最能反应土壤酸碱性状。

    Further analysis of the main composition method shows that among the main composition the available N has the main function . In the sour alkali characteristics , the pH shows the character of sour alkaline of soil most obviously .

  25. 采用了局部保持投影(LPP)算法和经典的主成分分析(PCA)算法对三维人脸深度图像进行特征提取。

    And using Locality Preserving Projections ( LPP ) algorithm and classical Principal Component Analysis ( PCA ) algorithm extract feature in 3D face depth image .

  26. 针对设计矩阵的多重共线性问题,为了改进基于最小二乘估计的统计诊断量Cook距离,提出了基于Massy主成分下的Cook距离(MPCC距离)。

    In the light of the approximate multicollinearity of matrix , distance for principal components estimation ( namely distance ) is put forward .

  27. 为提高工程图识别中基于主成分分析(PCA)的特征提取的精度,讨论了PCA鲁棒性问题的两种提法。

    One way to improve the robustness of principal component analysis ( PCA ) is studied in order to increase the accuracy of feature extraction based on PCA in engineering image recognition .

  28. 论文使用SPSS和excel进行指标筛选,剔除重复性较大和差异性较小的指标,构成新的指标评价体系,再用主成分聚类法对各城市商贸物流发展进行评价。

    Using SPSS and Excel for index selection , the paper constitutes a new evaluation index system , and then the clustering of each city commercial logistics development evaluation through Principal Component Clustering .

  29. 结合半固态加工基本原理,利用热力学计算方法,设计出了新型半固态铝合金,主成分为Al-6%Si-2%Mg,并利用实验方法优化选择了微量元素Zr、Sr。

    A main component Al-6 % Si-2 % Mg of an advanced semi-solid aluminum alloy was designed by thermodynamic calculations with the consideration of the basic principle of semi-solid processing ( SSP ) .

  30. 提出结合核主成分分析(KPCA)和自适应神经模糊推理系统(ANFIS)的色彩校正(KPCAANFIS)算法。

    An algorithm for color calibration was proposed by integrating an ANFIS ( adaptive-network-based fuzzy inference system ) with KPCA ( kernel principal component analysis ) .