主元

词组短语

pivot element

与主元相关的网络例句 [注：此内容来源于网络，仅供参考]

In the light of the complex, high-level and non-linear feature of the mathematical model which describe the transport of the coalbed methane, this paper study the fully-implicit solving method of the mathematical model in detail. Based on the complexity of the algebraic equations which are formed eventually, according to the alternating direction implicit difference pattern, this paper use the iterative method and the fully main element Gauss-Jordan eliminating method to solve equations, which is to use the iterative method to determine coefficient matrix and use the fully main element Gauss-Jordan method to solve th linear algebraic equation group, at the same time of studying the solving method of the mathematical model, according to the devising requirement of FORTRAN77 program structure, this paper draw up computer program and form the corresponding computer model, and verify the validity and reliability of the model in theory by operating the model.

重点研究了模型内、外边界及有关参数的处理，针对描述煤层甲烷运移的数学模型是一个复杂、高阶非线性数学模型的特点，详细研究了模型的全隐式求解方法，根据最后形成的代数方程组的复杂性，按交替方向隐式差分格式，采用迭代与全选主元高斯约当消去法相结合的方法求解方程：即确定系数矩阵采用迭代法，求解线性方程组时采用全选主元高斯约当消去法，在研究模型解法的同时按FORTRAN结构化程序设计的要求，编制计算机程序，形成相应的CBMRS计算机模型，并通过模型的运行从理论上证明了模型的正确性与可靠性。

After probability functions of principle component and error were determined, the generated model can be constructed using the expectation and maximization algorithm.

在利用主元分析作统计监控时，没有主元与变量之间的生成模型，出现了检测指标量度不一致且只能离线故障识别等缺陷。

Out PCA Gaussian elimination is my calculation A study prepared at the completion of the main-element Gauss elimination method to achi...

列主元高斯消去法是我学习计算方法A时编写的完成了列主元高斯消去法实现方程组求解。

The results are compared with the traditional methods, and prove that the new method can not only detect and eliminate the gross error, but also get better data reconciliation results.

将主元分析和小波变换的多尺度理论有机地结合起来，充分利用其各自优点，提出了基于多尺度主元分析的数据校正方法，实例研究结果表明，这是一种有效的数据校正方法。

Kernel principal component analysis can compute principal components in high-dimensional feature space by means of integral operators and nonlinear kernel functions.It can effectively capture the nonlinear relationship in the process variables.

核主元分析方法通过集成算子与非线性核函数计算高维特性空间的主元成分，有效捕捉过程变量中的非线性关系。

The paper adopts the learning method of MSVMs to classify the faults, which avoids the mathematical solution for the inverse mapping and acquires the fault information through intelligent method directly.

由于原始数据经过核主元的非线性映射后难以求得核主元空间到原始空间的逆映射，因此给故障诊断带来困难。

Then the reconstructed data are analyzed by multiple statistical indexes such as T2 or SPE to determine if the supervised process exceeds the normal control limits. If fault occurs, then the supervising program will alarm to prompt that the process has abnormal states. Because it is hard to get the inverse mapping from the kernel space to the original space after the original data are nonlinear mapped by the KPCA method, hence it is difficult to diagnose how the fault happened.

该方法首先构造系统正常时的核主元模型，然后将新的数据映射到该核主元模型，对数据进行重构，重构的数据用多元统计指标T2或SPE判断监测过程是否超出了正常的控制限，若有故障发生，则监测程序将给于警告，提示过程出现了异常操作状况。

PCA is not only used as feature extracting method (where process variables are subjected to multivariate normal distribution), but also as a tool for dimension reduction; BSA is used to extract independent features or process blind source signals from process information in information theory sense, which is more effective than PCA in describing the process.

主元分析方法不仅作为一种过程特征的提取方法（在过程信息服从多元正态分布的情况下），而且也作为一种过程数据降维的主要工具（在过程盲源信号提取的情况下）；盲源信号分析是从信息论的角度，从过程信息中提取出尽可能独立的过程特征信号或过程原始信源信号，它具有比主元分析更好的刻画过程运行特征的性能。

The principal components in PCA is decided by virtue of cumulative percent variance and multi-correlation coefficients. The improved PCA is applied to mycetozoan fermentation process monitoring and fault diagnosis.

利用主元相关变量残差统计量代替平方预测误差Q统计量，并采用累积方差贡献率及复相关系数确定PCA模型的主元数。

For the limitations of single-scale modeling in traditional principal components analysis, multi-scale principal components analysis was applied to the fault monitor and diagnosis in floating production storage and off-loading system.

针对传统主元分析单尺度建模的局限性，以小波分析和主元分析理论为基础，应用多尺度主元分析方法对浮式油轮生产储油卸油系统进行故障检测与诊断系统的设计与实现。

与主元相关的网络解释 [注：此内容来源于网络，仅供参考]

pivot in a column：列主元

列秩|column rank | 列主元|pivot in a column | 裂变矩阵方法|fission matrix method

pivot element：主元

namespace 名字空间 | pivot element 主元 | parameter 参数

pivot, pivotal element：主元

主型算子|operator of principal type | 主元|pivot, pivotal element | 主值|principal value

primary key：主码

I)超码(SUPER KEY)关系中能惟一标识每个元组的属性或属性组(集) 一个关系可能有多个超码;候选码(CANDIDATE KEY)关系中能惟一标识每个元组的最少属性或属性组 一个关系可能有多个候选码;主 码(Primary Key)从候选码中选择一个作为该关系的主码,

Prime component analysis：主元分析

首位级别:the prime class | 主元分析:Prime component analysis | 宰相制度:Prime minister system

principal divisor：主因子

主曲率方向 principal direction of curvature | 主因子 principal divisor | 主元[素] principal element

totally positive element：全正元

全正规空间|fully normal space | 全正元|totally positive element | 全主元|complete pivot

Yuen Biao：主 演 元彪

◎编 剧 元彬Yuen Bun | ◎主 演 元彪 Yuen Biao | 杨丽菁 Cynthia Khan

metalinguistic variable：元语言主变量

metalinguistic formula 元语言连接词 | metalinguistic variable 元语言主变量 | metalized resistor 金属膜电阻器

lumpers：主合派

他们被称为"主合派"(lumpers). 从林奈时期 起这两派一直争论不休,林奈本人是一个主合派,他在界以外只用了阶元等级结构的四 个层次(种,属,目,门)就能应付自然界的多样性. 目前甚至相当保守的分类学家也 确认了21个阶元等级(Simpson,