辅助变量

They will be used in different situation in complex loop control; second, proposed an analysis method to compose multiple loops which have major control variable and auxiliary variable into a large system loop.

其分别适宜于不同情况下的复杂系统中较复杂回路的具体控制；其次，提出将复杂过程系统中主控变量及辅助变量所在的多个回路统一构成一个系统"大回路"的分析方法。

Ordinary Kriging, Co-Kriging and OKR interpolations were conducted with 72 SOC data in the topsoil (0~10 cm) which was selected as an auxiliary variable, and 36 and 24 SOC data in the subsoil (10~20 cm) as target variables.

以72个上层(0~10 cm)SOC数据为辅助变量，分别以36个及24个下层(10~20 cm)SOC数据为目标变量，分别进行普通克里格、协同克里格及OKR插值分析。

The contents from the third chapter to the fifth chapter are the kernels which are a series of applications of generalized regression model and generalized regression estimator. At first, this paper constructs ratio model, linear regression model, post-stratified regression model and nonparametric regression model through different regressive relationship between auxiliary variable and study variable.

首先是依据辅助变量与研究变量之间回归关系的不同，分别建立比率模型、线性回归模型、事后分层回归模型和非参数回归模型，然后再利用第二章中推导出的广义回归估计理论，对各种回归模型辅助下(来源：A4bBC12论文网www.abclunwen.com)的估计方法进行了系统性研究，从而构成了模型辅助估计方法的整个研究体系。

The soft-measuring technique is systemically described from the following aspects: auxiliary variable selection, data processing, soft-measuring model construction and model correction. Moreover, in order to solve the problem of measuring temperature of aluminum electrolytic cell, the importation electric power and blanking velocity are selected as auxiliary variable, then the temperature estimated value of the electrolytic cell is calculated. An autoregressive model with controlled item based on Modern Time Series Analysis method is established.

从辅助变量选择、数据处理、软测量模型建立和模型修正等方面系统地介绍了软测量技术；并针对铝电解槽温度高、腐蚀性强、温度难以直接测量的问题，选择电解槽的输入电功率和下料速度作为辅助变量，利用现代时间序列分析法建立了带受控项目的自回归数学模型，从而计算出电解槽的温度估计值。

Based on the segmented unstructured model of Nosiheptide fermentation process, the secondary variables are selected according to the implicit function existence theorem. The on-line identification of fermentation phases is accomplished by using an indicator variable which is gained by mathematical inference, and for each phase, a local soft sensor model is developed.

首先以分阶段的诺西肽发酵过程非结构模型为基础，根据隐函数存在定理进行辅助变量的合理选择；然后利用经数学推导得到的指示变量"伪比生长率"完成发酵阶段的在线辨识，并采用神经网络构建出对应于各阶段的局部软测量模型。

Secondary variables selecting method based on PCA is researched, and then secondary variables selecting method based on Partial Least-Squares Regression is proposed.

并且研究了基于主元分析的辅助变量选择方法，提出了基于偏最小二乘回归的辅助变量的选择方法，采用两种方法分别对常压精馏塔航空煤油干点的辅助变量进行了选择比较。

It's pointed out that soft sensor will play more important role in field bus network control system. According to this, a crude solution was addressed. At last, we point out that soft sensor technology must used to build an information warehouse for the whole enterprise, combined with data fusion, data warehouse, data rectification and other related technologies. The main contributions of this dissertation are as follows: The background, requirement, and application situation of soft sensors are expounded, the theories, methods and skills of soft sensing technology are analyzed, and the fruits and problems in current soft sensor technologies are summarized. Some new methods of soft sensor is proposed: A principal component analysis-based secondary variable selection method are proposed; A new conception which modeling data should have gross error detection is addressed, and then a cluster analysis-based modeling data gross error detection method is given.

本文的主要贡献有：对软测量技术根据实践的要求进行了一定的理论研究，针对具体问题提出了新的方法：讨论了辅助变量选择问题，研究了基于主元分析的辅助变量选择方法，该方法克服了传统方法只能利用数学模型产生的仿真数据进行最优辅助变量选择的缺点，可以根据历史数据进行辅助变量选择；提出了建模数据显著误差侦破的概念，指出传统的显著误差侦破研究的是已知过程数学模型的情况，而建模时数学模型是未知的，但是直接来自现场的数据并不能保证不含显著误差，并用基于聚类分析的方法解决了该问题，该方法利用聚类分析原理，直接面对过程数据，不需以过程模型为基础，在此基础上给出了软测量建模过程中样本数据的处理方法。

KNN analysis was independent of the correlated regression model, but directly affected the model structure. Via KPCA as a middle layer, under the instruction of assorted result of the kernel function, the method was able to capture the high-ordered principal components among the secondary variables, and use SVR to establish a correlated regression model between the featured principal components and the primary variable.

KNN分析独立于后继回归模型，却又直接影响模型结构，KPCA作为中间层，在KNN分类结果指导下提取不同类别包含辅助变量高阶信息的特征主元，然后使用SVR建立特征主元和主导变量之间的回归模型。

Then product between the plant height and stem-diameter of sunflower is marked as the integrated index and regarded as primary variable. Choosing water conter and EC as secondary variable, the integrated index of sunflower is estimated using the three variables CK method that is in the form of covariance function.

将向日葵株高与茎粗的乘积记为综合性指标并视为主变量，选取土壤含水率与EC值为辅助变量，分别运用CK法与普通克立格法(Ordinary Kriging，简记为OK法)对向日葵综合性指标进行预测研究。

In the whole process, Behavioral Variables should act as the main variables, and Demographic Variables, Geographic Variables, Psychographic Variables as auxiliary variables.

认为技术创新市场细分变量选择时应该以行为变量作为主变量，以地理区域变量、人口和社会变量以及心理变量作为辅助变量。

Do you know, i need you to come back

你知道吗，我需要你回来

Yang yinshu、Wang xiangsheng、Li decang,The first discovery of haemaphysalis conicinna.

1〕 杨银书，王祥生，李德昌。安徽省首次发现嗜群血蜱。