Model-sensitive sequential optimal designs

The increasing number of experimenters using computer-generated experimental designs creates an increasing need to have design procedures that are less sensitive to model misspecification. To address this problem, the notion of empirical models that have both important and potential terms is used. A two-stage design strategy for planning experiments in the face of model uncertainty is proposed. The advantage of this procedure resides in the rearrangement of active potential terms at the end of the first stage using marginal posterior probabilities of different candidate models. The two-stage procedure has better estimation efficiency than its one-stage alternatives available from the literature.     

Fuzzy clusterwise linear regression analysis with symmetrical fuzzy output variable

The traditional regression analysis is usually applied to homogeneous observations. However, there are several real situations where the observations are not homogeneous. In these cases, by utilizing the traditional regression, we have a loss of performance in fitting terms. Then, for improving the goodness of fit, it is more suitable to apply the so-called clusterwise regression analysis. The aim of clusterwise linear regression analysis is to embed the techniques of clustering into regression analysis. In this way, the clustering methods are utilized for overcoming the heterogeneity problem in regression analysis. Furthermore, by integrating cluster analysis into the regression framework, the regression parameters (regression analysis) and membership degrees (cluster analysis) can be estimated simultaneously by optimizing one single objective function. In this paper the clusterwise linear regression has been analyzed in a fuzzy framework. In particular, a fuzzy clusterwise linear regression model (FCWLR model) with symmetrical fuzzy output and crisp input variables for performing fuzzy cluster analysis within a fuzzy linear regression framework is suggested. For measuring the goodness of fit of the suggested FCWLR model with fuzzy output, a fitting index is proposed. In order to illustrate the usefulness of FCWLR model in practice, several applications to artificial and real datasets are shown.     

浅析PowerInspect测量基准的建立

本文介绍了PowexInspect建立基准的3种主要方法（PLP Bestfit RPS），就每种方法的实际应用进行了有针对性的讨论，并用深入浅出的语言解释了其中所涉及到的主要数学算法，尤其是对RPS方法的深入应用提出了一些轮廓性的想法。     

基于局部模型网络的超声波浓度测量和在线校正

在很多情况下 ,液体浓度是其声速的函数 ,而且在不同的温度点上 ,这种函数关系是不同的 .针对浓度、声速和温度关系的这种特点 ,本文提出了基于局部模型网络的浓度和声速、温度关系的拟合和校正方法 .这种方法比普通的多项式拟合具有更多的灵活性和适用性 ,易于在线进行 .     

调整轴承配合公差提高电机装配质量

电机轴承的装配精度是影响电机装配质量的主要因素之一,通过评价轴承室和轴承档的原设计思想和分析实际加工情况,提出以修改端盖轴承室及转轴轴承档的尺寸公差来取得理想的径向游隙的设计思想。实践证明,该方法能提高轴承的装配精度,达到改善电机噪声的目的。     

用最小二乘法求零应力状态下动脉壁本构方程

由动脉血管零应力状态和无载荷状态的几何参数，分析计算了其无载荷状态下的残余应变，并由残余应变分布和平衡方程，用最小二乘法拟合七参数应变能密度函数的参数，进而确定了动脉壁在零应力状态下的本构方程。     

单井黑油模型自动历史拟合的一种方法

提出了单井三维三相黑油模型自动历史拟合的一种方法。在此基础上，建立了一个带约束条件的非线性目标函数，应用本算法使目标函数达到最小，实现自动历史拟合，从而反求出地层各参数值，另外还对新疆百口泉井的测试资料进行了自动历史拟合，求得了各自地层参数值，同时将本文结果与地层参数电测解释结果进行了对比，证实了本算法求解的可靠性。     

线性拟合解谱时σ的选取及其对峰位漂移所造成误差的补偿作用

用线性拟合法分析核素能谱时,标准偏差σ是一个重要的参数。本文介绍了如何选取σ的方法,说明了它对峰位漂移所造成误差的补偿作用。     

光栅投影式3维照相系统中光栅投影仪的标定

提出了一种光栅投影式立体照相系统中光栅投影平面的标定方法。将光栅投影到已知目标平面,通过数字摄影得到光栅平面与目标平面相交的光栅图像。根据光栅图像记录的信息,在每条交线上提取两点,作为对应光栅平面拟合用的两点。按一定规律移动目标平面,即可得到每个光栅平面上若干对点。利用最小二乘法分别拟合出每个光栅平面的空间平面方程。