倾斜卧式储油罐的罐容表标定

探讨圆形封头卧式储油罐发生纵向变位α和横向偏转β的罐容表的标定问题,建立卧式储油罐的储油量与油位高度H0及变位参数α,β的函数模型和近似模型;根据给定的一组实测数据,利用最小二乘法原理得到了变位参数α,β,进而标定了新的罐容表,并分析误差证实了模型的可靠性。     

储油罐的变位识别与罐容表标定

研究了储油罐的变位识别与罐容表标定的问题.针对问题一,利用求体积的定积分法,求出了罐体在无变位与纵向变位两种情况下分别关于油位高度及纵向倾斜角的体积表达式,得出了无变位和纵向倾斜角为α=4.1°两种情况下的罐容表标定值.针对问题二,利用非线性最小二乘法得到两个偏转角,并制定出罐体变位后油位高度的罐容表标定值.     

储油罐的变位识别与罐容表标定之建模与分析

通过建立数学模型明确了储油罐的变位对罐容表的影响,较好的处理和分析了罐容表的重新标定问题。首先,对于椭圆型储油罐模型,求出罐体无变位时的理论模型,进行修正,得到了较为准确的修正模型。横向变位β的理论模型。利用实测数据,最小二乘法和变步长收缩方法,求得了相应的角度α=2.1°,β=4.4°,得到了真正的实际模型。最后给出了一个实时观测、处理、修正油罐发生变位时油量标定的系统方法。     

储油罐的变位分析与罐容表标定

研究了地下卧式储油罐在发生变位情况下的油位与油量的关系,利用罐体的轴向截面实施微元分析,建立起在纵向倾斜变位和横向偏转变位情况下的油量计算公式,并对照实验数据分析油位探针的计量误差,给出了校正的方法;根据实际储油罐的检测数据,构建最小二乘法数学模型,以确定未知的变位参数,并应用这些理论分析结果,对发生变位的小型椭圆储油罐和大型实际储油罐分别制定了新的罐容表标定值。     

储油罐变位后油量的计算模型与校正方法

探讨储油罐的变位识别与罐容表标定问题。通过设置合适的坐标系,使用截面分析和近似简化、坐标变换等技巧,推导出椭圆型小储油罐和实际储油罐在发生变位时,储油量与油高之间的函数关系;对照理论计算与实验数据,发现非线性误差,运用函数拟合,对模型做出修正,并利用实验数据验证了修正的有效性;针对实际储油罐的测量数据,通过最小二乘法确定油罐的变位参数,并对数据结果进行了具体分析。     

静态最小二乘法及其应用

给出静态最小二乘法原理,理论推导过程和最小二乘法公式,通过实例验证最小二乘法的有效性和实用性。介绍了静态最小二乘法具有的局限性、动态最小二乘法的诞生及最小二乘法理论的发展。     

线性最小二乘问题求解讨论

通过最小二乘准则及线性最小二乘拟合问题的引入,给出了超定方程组及最小二乘问题的概念,同时给出了最小二乘解的定义。讨论了最小二乘问题与法方程组的解的关系,并指出了极小最小二乘解及其解的表达式,着重讨论了法方程组的病态问题。研究的结论,给出了较稳定的算法——4R算法,有改进的正交化方法和左乘H法。     

最小二乘法原理及其在实验曲线拟合中的应用分析

最小二乘法在曲线拟合中占有十分重要的位置,在一元一次直线方程中,最小二乘法的应用十分广泛,但在一元二次的直线方程中应用有限,本文从最小二乘法在直线中应用出发,引进一元二次方程进行论述,从物理学角度将所得物理模型进行论证,最终通过校验说明文章模型的合理性。     

线性回归中的的多重共线性

多元线性回归中自变量之间的多重共线性问题在我们实际运用中很容易产生,为了解决这个问题,常用的方法是最小二乘回归.本文以根据分析结果总结出最小二乘回归对解决这一问题的缺点的不足.而偏最小二秉回归法是最小二乘法的一种改进,在变量数目巨大的情况下,如果数据中变量的个数多,偏最小二乘回归的优点更能充分的显示出来     

最小二乘法与线性回归

本文介绍了最小二乘法的基本原理,并从一元线性回归入手讨论了物理实验中用最小二乘法处理数据的方法。     

Parameter Recovery in the Graded Response Model Using MULTILOG

The graded response model can be used to describe test-taking behavior when item responses are classified into ordered categories. In this study, parameter recovery in the graded response model was investigated using the MULTILOG computer program under default conditions. Based on items having five response categories, 36 simulated data sets were generated that varied on true θ distribution, true item discrimination distribution, and calibration sample size. The findings suggest, first, the correlations between the true and estimated parameters were consistently greater than 0.85 with sample sizes of at least 500. Second, the root mean square error differences between true and estimated parameters were comparable with results from binary data parameter recovery studies. Of special note was the finding that the calibration sample size had little influence on the recovery of the true ability parameter but did influence item-parameter recovery. Therefore, it appeared that item-parameter estimation error, due to small calibration samples, did not result in poor person-parameter estimation. It was concluded that at least 500 examinees are needed to achieve an adequate calibration under the graded model.     

偏最小二乘多元校正法用于三组分食用色素的同时测定

将偏最小二乘法(PLS)与可见分光光度法相结合,对胭脂红、苋菜红、日落黄三种食用色素进行不经分离的同时定量分析。使用交叉验证法选择主成分数建立了校正模型,预测结果令人满意。采用随机抽样方法研究了校正模型中样品集和样本容量对预测能力的影响,结果表明,在文章所研究的体系中,偏最小二乘法的预测能力不因样品集和样本容量的不同而有明显差异,从而说明了文章所用方法具有较大的可靠性和适用性。     

校正变换矩阵法用于多组分染色剂的同时测定研究

将校正变换矩阵法(CTM)与可见分光光度法相结合,对藏红、荧光桃红、曙红三种染色剂进行不经分离同时测定.使用交叉验证法选择主因子数建立了校正模型,预测结果令人满意.在相同条件下,将校正变换矩阵法与偏最小二乘(PLS)回归的结果进行了比较,结果表明两种方法的预测准确性没有显著性差异.     

On-site variety discrimination of tomato plant using visible-near infrared reflectance spectroscopy

The use of visible-near infrared (NIR) spectroscopy was explored as a tool to discriminate two new tomato plant varieties in China (Zheza205 and Zheza207).In this study,82 top-canopy leaves of Zheza205 and 86 top-canopy leaves of Zheza207 were measured in visible-NIR reflectance mode.Discriminant models were developed using principal component analysis (PCA),discriminant analysis (DA),and discriminant partial least squares (DPLS) regression methods.After outliers detection,the samples were randomly split into two sets,one used as a calibration set (n=82) and the remaining samples as a validation set (n=82).When predicting the variety of the samples in validation set,the classification correctness of the DPLS model after optimizing spectral pretreatment was up to 93%.The DPLS model with raw spectra after multiplicative scatter correction and Savitzky-Golay filter smoothing pretreatments had the best satisfactory calibration and prediction abilities (correlation coefficient of calibration (Rc)=0.920,root mean square errors of calibration=0.196,and root mean square errors of prediction=0.216).The results show that visible-NIR spectroscopy might be a suitable alternative tool to discriminate tomato plant varieties on-site.     

Prediction of valid acidity in intact apples with Fourier transform near infrared spectroscopy

INTRODUCTION Consumers’ acceptance of fresh or processedapples is the ultimate goal of apple breeders, foodscientists and supermarket managers. Internal qualityassessment has focused on two major objectives:removal of fruit with internal defects and taste selec-tion. Three major parameters including sugar content,acidity and firmness have to be taken into account todetermine the internal quality and the taste of an apple.Near infrared spectroscopy has been used to measureseveral properti…     

Prediction of valid acidity in intact apples with Fourier transform near infrared spectroscopy

To develop nondestructive acidity prediction for intact Fuji apples, the potential of Fourier transform near infrared (FT-NIR) method with fiber optics in interactance mode was investigated. Interactance in the 800 nm to 2619 nm region was measured for intact apples, harvested from early to late maturity stages. Spectral data were analyzed by two multivariate calibration techniques including partial least squares (PLS) and principal component regression (PCR) methods. A total of 120 Fuji apples were tested and 80 of them were used to form a calibration data set. The influences of different data preprocessing and spectra treatments were also quantified. Calibration models based on smoothing spectra were slightly worse than that based on derivative spectra, and the best result was obtained when the segment length was 5 nm and the gap size was 10 points. Depending on data preprocessing and PLS method, the best prediction model yielded correlation coefficient of determination (r^2) of 0.759,low root mean square error of prediction (RMSEP) of 0.0677, low root mean square error of calibration (RMSEC) of 0.0562. The results indicated the feasibility of FT-NIR spectral analysis for predicting apple valid acidity in a nondestructive way.     

Explaining calibration accuracy in classroom contexts: the effects of incentives, reflection, and explanatory style

A 2 × 2 quasi-experimental design was used to investigate the impact of extrinsic incentives and reflection on students’ calibration of exam performance. We further examined the relationships among attributional style, performance, and calibration judgments. Participants were 137 college students enrolled in an educational psychology course. Results differed as a function of exam performance. Higher-performing students were very accurate in their calibration and did not show significant improvements across a semester-length course. Attributional style did not significantly contribute to their calibration judgments. Lower-performing students, however, were less accurate in their calibration, and students in the incentives condition showed significant increases in calibration. Beyond exam scores, attributional style constructs were significant predictors of calibration judgments for these students. The constructs targeting study and social variables accounted for most of the additional explained variance. The qualitative data also revealed differences by performance level in open-ended explanations for calibration judgments.     

ATLAB软件在传感器实验教学中的应用

本文针对传感器实验教学中存在的数据处理难的问题,利用MATLAB软件给出了传感器实验数据的处理和标定的方法和实例,介绍了cftool具箱的功能,并应用到传感器标定中的拟合、绘图和建模工作中。我们编写了相关程序,计算了非线性误差、灵敏度和滞后误差等传感器静态标定指标。这对传感器综合性实验和开放性实验内容的丰富提供了一种新的思路。