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基于知识的变结构解耦 1

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多普勒超声心动图 1

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Multivariable regression model for Fox depth correction factor

Ravi Kant MITTAL, Sanket RAWAT, Piyush BANSAL

《结构与土木工程前沿（英文）》 2019年第13卷第1期页码 103-109 doi: 10.1007/s11709-018-0474-6

摘要： This paper presents a simple and efficient equation for calculating the Fox depth correction factor used in computation of settlement reduction due to foundation embedment. Classical solution of Boussinesq theory was used originally to develop the Fox depth correction factor equations which were rather complex in nature. The equations were later simplified in the form of graphs and tables and referred in various international code of practices and standard texts for an unsophisticated and quick analysis. However, these tables and graphs provide the factor only for limited values of the input variables and hence again complicates the process of automation of analysis. Therefore, this paper presents a non-linear regression model for the analysis of effect of embedment developed using “IBM Statistical Package for the Social Sciences” software. Through multiple iterations, the value of coefficient of determination is found to reach 0.987. The equation is straightforward, competent and easy to use for both manual and automated calculation of the Fox depth correction factor for wide range of input values. Using the developed equation, parametric study is also conducted in the later part of the paper to analyse the extent of effect of a particular variable on the Fox depth factor.

关键词： settlement embedment Fox depth correction factor regression multivariable

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基于知识的多变量非线性系统变结构解耦控制

涂承媛,曾衍钧

《中国工程科学》 2001年第3卷第10期页码 48-52

摘要：

文章提出了一种基于知识的变结构解耦控制策略，并用于多变量非线性系统的控制，避免了传统解耦控制所必须的建模过程，特别是避免了相应的大量复杂的矩阵运算。阐述了其控制知识库中的一些模块，给出了其算法要点。提出的策略成功地用于一个3×3强耦合系统一三绕组加热标准温度源的恒温控制，得到了温度稳定性和温度均匀性都优于1℃的效果，这是传统方法用于该系统所无法实现的。

关键词：多变量非线性系统解耦控制基于知识的变结构解耦

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Assessment of temporal and spatial variations in water quality using multivariate statistical methods: a case study of the Xin'anjiang River, China

Xue LI,Pengjing LI,Dong WANG,Yuqiu WANG

《环境科学与工程前沿（英文）》 2014年第8卷第6期页码 895-904 doi: 10.1007/s11783-014-0736-z

摘要： This study evaluated the temporal and spatial variations of water quality data sets for the Xin'anjiang River through the use of multivariate statistical techniques, including cluster analysis (CA), discriminant analysis (DA), correlation analysis, and principal component analysis (PCA). The water samples, measured by ten parameters, were collected every month for three years (2008–2010) from eight sampling stations located along the river. The hierarchical CA classified the 12 months into three periods (First, Second and Third Period) and the eight sampling sites into three groups (Groups 1, 2 and 3) based on seasonal differences and various pollution levels caused by physicochemical properties and anthropogenic activities. DA identified three significant parameters (temperature, pH and ) to distinguish temporal groups with close to 76% correct assignment. The DA also discovered five parameters (temperature, electricity conductivity, total nitrogen, chemical oxygen demand and total phosphorus) for spatial variation analysis, with 80.56% correct assignment. The non–parametric correlation coefficient (Spearman R) explained the relationship between the water quality parameters and the basin characteristics, and the GIS made the results visual and direct. The PCA identified four PCs for Groups 1 and 2, and three PCs for Group 3. These PCs captured 68.94%, 67.48% and 70.35% of the total variance of Groups 1, 2 and 3, respectively. Although natural pollution affects the Xin'anjiang River, the main sources of pollution included agricultural activities, industrial waste, and domestic wastewater.

关键词： Xin'anjiang River multivariable statistical analysis temporal variation spatial variation water quality

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基于一种全新的优化多变量非等距模型对中国汉族成人左心室多普勒超声心动图测值生理性变异的校正方法 Article

姚桂华, 陈湘云, 杨文静, 张青, 刘静, 梁欢, 孙慧, 许耀, 王丽, 徐金锋, 张澄, 孙丰荣, 张梅, 曾雪迎, 张运

《工程（英文）》 2022年第16卷第9期页码 115-122 doi: 10.1016/j.eng.2021.05.007

摘要：

多数左心室（LV）多普勒超声心动图参数测值随年龄和性别显著变化，因此有必要对其生理性差异进行校正。本研究旨在验证：不同的多普勒参数测值与生物学特征变量间呈异速非线性相关，且其校正常数与校正指数各不同。共测量了1224名健康成人的23个LV多普勒参数。随机选择70%数据（A组）建立优化多变量非线性模型（OMAM），在30%数据（B组）和183名超重人群数据（C组）中验证OMAM的可靠性，并与基于体表面积（BSA）的单变量等距模型（SVIM）进行比较。结果显示，校正前，23个LV多普勒参数均与一个或多个生物学特征变量显著相关，B组中47.8% (11/23)的参数存在性别间差异，经OMAM校正后，81.8% (9/11)的参数消除了性别间差异。OMAM对B组和C组数据的校正成功率分别为100% (23/23)和82.6% (19/23)，建立了独立于生物学特征变量的多普勒参数的OMAM参考值，而基于BSA的SVIM校正成功率为零。不同的LV多普勒参数与一个或多个生物学特征变量呈异速非线性相关；本研究建立的OMAM成功校正了因生物学特征变量差异对健康和超重人群多普勒测值的生理性影响，其校正效果显著优于传统的SVIM。然而，OMAM针对其他种族、肥胖和疾病状态人群的适用性仍需进一步探究

关键词：多普勒超声心动图生理性变异非等距模型正常参考值