Estimation of mass transfer coefficient in ozone absorption by linear least square fitting and Simplex search methods

For physical ozone absorption without reaction,two parametric estimation methods,i.e.the common linear least square fitting and non-linear Simplex search methods,were applied,respectively,to determine the ozone mass transfer coefficient during absorption and both methods give almost the same mass transfer coefficient.While for chemical absorption with ozone decomposition reaction,the common linear least square fitting method is not applicable for the evaluation of ozone mass transfer coefficient due to the difficulty of model linearization for describing ozone concentration dissolved in water.The nonlinear Simplex method obtains the mass transfer coefficient by minimizing the sum of the differences between the simulated and experimental ozone concentration during the whole absorption process,without the limitation of linear relationship between the dissolved ozone concentration and absorption time during the initial stage of absorption.Comparison of the ozone concentration profiles between the simulation and experimental data demonstrates that Simplex method may determine ozone mass transfer coefficient during absorption in an accurate and high efficiency way with wide applicability.

Linear-fitting-based similarity coefficient map for tissue dissimilarity analysis in T2^＊-w magnetic resonance imaging

Similarity coefficient mapping（SCM） aims to improve the morphological evaluation of T＊2weighted magnetic resonance imaging（T＊2-w MRI）. However, how to interpret the generated SCM map is still pending. Moreover, is it probable to extract tissue dissimilarity messages based on the theory behind SCM？ The primary purpose of this paper is to address these two questions. First, the theory of SCM was interpreted from the perspective of linear fitting. Then, a term was embedded for tissue dissimilarity information. Finally, our method was validated with sixteen human brain image series from multiecho T＊2-w MRI. Generated maps were investigated from signal-to-noise ratio（SNR） and perceived visual quality, and then interpreted from intra- and inter-tissue intensity. Experimental results show that both perceptibility of anatomical structures and tissue contrast are improved. More importantly, tissue similarity or dissimilarity can be quantified and cross-validated from pixel intensity analysis. This method benefits image enhancement, tissue classification, malformation detection and morphological evaluation.

Research on the Model of Linear Data Fitting Method

By using the method of least square linear fitting to analyze data do not exist errors under certain conditions, in order to make the linear data fitting method that can more accurately solve the relationship expression between the volume and quantity in scientific experiments and engineering practice, this article analyzed data error by commonly linear data fitting method, and proposed improved process of the least distance squ^re method based on least squares method. Finally, the paper discussed the advantages and disadvantages through the example analysis of two kinds of linear data fitting method, and given reasonable control conditions for its application.

函数系数自回归模型推广形式的Back-Fitting估计

文章针对时间序列中函数系数自回归模型给出其推广形式,借助向后拟合的思想介绍推广形式中函数系数部分和参数部分的估计,该方法可以得到模型中的常值系数估计量的精确表达式;并通过一个数值模拟表明所提出的估计方法具有可行性和稳定性。

Displacement Response Reconstruction of Slender Flexible Structures Based on Cubic Spline Fitting Method

How to reconstruct a dynamic displacement of slender flexible structures is the key technology to develop smart structures and structural health monitoring(SHM), which are beneficial for controlling the structural vibration and protecting the structural safety. In this paper, the displacement reconstruction method based on cubic spline fitting is put forward to reconstruct the dynamic displacement of slender flexible structures without the knowledge of modeshapes and applied loading. The obtained strains and displacements are compared with the results calculated by ABAQUS to check the method's validity. It can be found that the proposed method can accurately identify the strains and displacement of slender flexible structures undergoing linear vibrations, nonlinear vibrations, and parametric vibrations. Under the concentrated force, the strains of slender flexible structures will change suddenly along the axial direction. With locally densified measurement points, the present reconstruction method still works well for the strain concentration problem.

The Parameters Fitting in High-strength Concrete Mix Proportion Experiment

Parameters that need to be fitted in High-Strength concrete mix proportion expe riment and two equation models that are referenced in the experiment are discuss ed. The reasoning and implement of the corresponding linear fitting algorithm ar e demonstrated.Parmeter fitting is realized by value estimate method of mathemat ical statistics.This paper combines mathematical statisitics,linear equations an d template thought together successfully and discussed an efficient parameter fi tting method based on strength equation model and water consumption equation mod el.

Study on Variation of Fitting Goodness of Relation Between Earthquake Frequency and Magnitude before Moderately Strong Earthquakes (Ms≥5.0)

In this paper,characteristics of spatial and temporal variation of linear fitting goodness before some moderately strong earthquakes(Ms≥5.0)in the eastern part of China(east of longitude 180)are studied according to the famous Gutenberg-Richter’s relation expressed as lgN=a-bM,by using the moderate and small events that occurred in and around the source area.The results show that the linear goodness of fitting varies abnormally prior to these moderately strong earthquakes.In the early stage of the earthquake preparatory process,distribution of the energy released through small events in and around the source area is isostatic and the fitting goodness approximates 1,while the distribution of the energy turns to be isostatic before moderately strong earthquakes,leading to the obvious decrease of the linear goodness of fitting.This phenomenon could be a medium term anomaly and a medium term criterion for moderately strong earthquake prediction.

An Interesting Fitting Formula of Quark Masses

We show an interesting empirical formula of quark masses here, which is obtained by implementing the east squares fit. In this formula the measured QCD coupling is almost a ＂best fitting coupling＂.

半变系数模型的Back-Fitting估计

针对半变系数回归模型给出了一种后向拟合方法,该方法可得到模型中常值系数估计量的精确表达式;同时给出了实验设计方法和数值模拟结果,用于验证所提出的估计方法对估计常值系数具有满意的精度和稳定性.

洛阳盾构隧道地表沉降Peck公式参数修正

为准确预测洛阳粉质黏土与砂卵石复合地层中的盾构隧道地表沉降量,采用线性回归拟合方法,对洛阳地铁某区间隧道盾构掘进时的地表沉降监测数据进行拟合,引入地表最大沉降修正系数α和沉降槽宽度修正系数β对单线Peck公式进行修正。结果表明:针对单线隧道,采用线性回归方法拟合隧道横断面地表沉降得到的曲线与实际监测数据吻合度高,当修正系数α为0.4~0.9、β为0.5~0.7时得到的修正Peck公式精度最高;针对双线隧道,该地层下的地表沉降基本呈双峰“W”形,双线隧道的土体损失率η和沉降槽宽度系数K的分布区间分别为0.2%~0.8%和0.2~0.5,平均值分别为0.45%和0.37,且先行线的土体损失率均值、沉降槽宽度系数均值分别为后行线的1.4倍、1.3倍。研究成果可为洛阳典型粉质黏土与砂卵石复合地层中盾构隧道后续施工提供数据支撑。

DFIT测试在长庆气田开发中的应用

与常规的小型测试压裂不同,流体注入诊断测试(DFIT)是通过关井阶段出现的拟线性流或拟径向流阶段求取储层压力,采用改进的梅耶霍夫方法(M-method)解释储层渗透率。以长庆榆林气田一口开发井为例,依据DFIT的技术原理和测试步骤,对该并测试压降数据进行解释分析,结果可信度较高,证明了该项工艺在长庆低压低渗油气田的可行性。

身体活动阶段理论的阶段有效性评估:以“从无活动到保持活动的四步骤(FIT)模型”为例

本研究从阶段算法测量有效性和阶段特征两个方面,对"从无活动到保持活动的四步骤模型"(FIT模型)的阶段有效性进行全面评估。前者检验FIT模型的阶段算法是否可以将个体正确划分为"活动者"和"不活动者",后者检验社会心理学变量是否随身体活动阶段变化表现出非连续性模式和非线性趋势。本研究采用横断性研究设计,以中德两国2082名成年人为研究被试(年龄:M=38.7,SD=8.67;中国人:1206人,57.9%),采用敏感性、特异性、受试者工作特征曲线(ROC曲线)、曲线下面积值(AUC值)和卡方检验考察阶段算法测量有效性及其在人口统计学变量上的差异性。此外,采用先验对比检验和趋势检验对阶段特征进行考察。研究结果包括:(1)在阶段算法测量有效性方面,敏感性指标为92.8%,特异性指标为81.5%,AUC值为0.93,表明FIT模型的阶段算法在区分活动者和不活动者上,具有较高的判别力。此外,敏感性和特异性在年龄和性别上差异均不显著,但在国籍和受教育程度上有显著差异。(2)在先验对比检验中,社会心理学变量在阶段上的非连续性模式得到证实。它们在相邻阶段间关系的假设有67.4%得到验证。在趋势检验中,所有社会心理学变量均出现显著的二次方及以上趋势,其非线性趋势得到证实。本研究在一定程度上验证了FIT模型的阶段有效性,为今后基于FIT模型身体活动阶段分类,设计阶段匹配性干预,促进成年人参与和坚持身体活动提供了理论依据。

线性测量误差模型的lack-of-fit检验

基于正态假设 ,提出了测量误差模型lack of fit检验的一种方法 .在原假设下 ,检验统计量渐近服从 χ2 分布 .还就该检验的势函数与权函数的选择进行了讨论 。

A comparison of piecewise cubic Hermite interpolating polynomials,cubic splines and piecewise linear functions for the approximation of projectile aerodynamics

Modelling and simulation of projectile flight is at the core of ballistic computer software and is essential to the study of performance of rifles and projectiles in various engagement conditions.An effective and representative numerical model of projectile flight requires a relatively good approximation of the aerodynamics.The aerodynamic coefficients of the projectile model should be described as a series of piecewise polynomial functions of the Mach number that ideally meet the following conditions:they are continuous,differentiable at least once,and have a relatively low degree.The paper provides the steps needed to generate such piecewise polynomial functions using readily available tools,and then compares Piecewise Cubic Hermite Interpolating Polynomial(PCHIP),cubic splines,and piecewise linear functions,and their variant,as potential curve fitting methods to approximate the aerodynamics of a generic small arms projectile.A key contribution of the paper is the application of PCHIP to the approximation of projectile aerodynamics,and its evaluation against a set of criteria.Finally,the paper provides a baseline assessment of the impact of the polynomial functions on flight trajectory predictions obtained with 6-degree-of-freedom simulations of a generic projectile.

A self-adaptive linear evolutionary algorithm for solving constrained optimization problems

In many real-world applications of evolutionary algorithms,the fitness of an individual requires a quantitative measure.This paper proposes a self-adaptive linear evolutionary algorithm （ALEA） in which we introduce a novel strategy for evaluating individual＇s relative strengths and weaknesses.Based on this strategy,searching space of constrained optimization problems with high dimensions for design variables is compressed into two-dimensional performance space in which it is possible to quickly identify ＇good＇ individuals of the performance for a multiobjective optimization application,regardless of original space complexity.This is considered as our main contribution.In addition,the proposed new evolutionary algorithm combines two basic operators with modification in reproduction phase,namely,crossover and mutation.Simulation results over a comprehensive set of benchmark functions show that the proposed strategy is feasible and effective,and provides good performance in terms of uniformity and diversity of solutions.

Parker Test for Heteroskedasticity Based on Sample Fitted Values

To address the drawbacks of the traditional Parker test in multivariate linear models: the process is cumbersome and computationally intensive, we propose a new heteroscedasticity test. A new heteroskedasticity test is proposed using the fitted values of the samples as new explanatory variables, reconstructing the regression model, and giving a new heteroskedasticity test based on the significance test of the coefficients, it is also compared with the existing Parker test which is improved using the principal component idea. Numerical simulations and empirical analyses show that the improved Parker test with the fitted values of the samples proposed in this paper is superior.

An adaptive genetic algorithm for solving bilevel linear programming problem

Bilevel linear programming, which consists of the objective functions of the upper level and lower level, is a useful tool for modeling decentralized decision problems. Various methods are proposed for solving this problem. Of all the algorithms, the ge- netic algorithm is an alternative to conventional approaches to find the solution of the bilevel linear programming. In this paper, we describe an adaptive genetic algorithm for solving the bilevel linear programming problem to overcome the difficulty of determining the probabilities of crossover and mutation. In addition, some techniques are adopted not only to deal with the difficulty that most of the chromosomes maybe infeasible in solving constrained optimization problem with genetic algorithm but also to improve the efficiency of the algorithm. The performance of this proposed algorithm is illustrated by the examples from references.

A fault recognition method based on clustering linear regression

Aiming at the problems of low accuracy,long time consumption,and failure to obtain quantita-tive fault identification results of existing automatic fault identification technic,a fault recognition method based on clustering linear regression is proposed.Firstly,Hough transform is used to detect the line segment of the enhanced image obtained by the coherence cube algorithm.Secondly,the endpoint of the line segment detected by Hough transform is taken as the key point,and the adaptive clustering linear regression algorithm is used to cluster the key points adaptively according to the lin-ear relationship between them.Finally,a fault is generated from each category of key points based on least squares curve fitting method to realize fault identification.To verify the feasibility and pro-gressiveness of the proposed method,it is compared with the traditional method and the latest meth-od on the actual seismic data through experiments,and the effectiveness of the proposed method is verified by the experimental results on the actual seismic data.

基于线结构光扫描的烟支表面缺陷检测方法研究

在烟支表面缺陷检测时,为解决传统二维图像方法无法获得深度信息的问题,提出一种基于线结构光传感器旋转扫描的检测方法。烟支在两同向辊轮的旋转带动下实现自转,通过线结构光视觉传感器获取物体轴向轮廓线,使用随机采样一致性拟合轮廓线,通过计算原始点到拟合轮廓的距离判断缺陷点。选取某品牌烟支在检测过程中得到的原始数据,其中多组样本的Kappa值均达到0.97,重复性达到99.3%。研究为烟支缺陷检测提供参考。

基于幂加权最小二乘拟合的红外相机辐射定标方法

分析了现有线性度计算方法的不足,提出基于偏差/测量值的新线性度评价方式,通过该方式最小二乘拟合的低端温度偏差比高端大一个数量级,并采用加权拟合提高系统响应线性度。在分析不同光谱的温度和辐亮度拟合函数基础上,提出一种基于辐亮度倒数幂加权最小二乘线性拟合的地面和星上辐射定标方法,确认最佳权重幂次,建立了幂次n=1的加权最小二乘拟合外黑体线性定标方程、内黑体线性定标方程、内外黑体辐亮度转换模型。针对星上内黑体高精度两点定标建立了基于加权最小二乘拟合内外黑体辐亮度转换模型;针对星上黑体发射率退化提出了基于恒星定标的红外相机星上内黑体辐亮度定标修正方法,建立了外黑体辐亮度、内黑体辐亮度和恒星辐亮度转换模型。采用加权线性拟合后,积分时间10 ms的低温端外黑体反演偏差由1.63 K下降到0.52 K,内黑体偏差反演温度偏差由0.83 K下降到0.39 K,系统响应线性度明显提升。