最小二乘法的改进算法辨识棱镜摄谱仪定标多项式

提出了采用最小二乘法的改进算法拟和一元非线性函数,并用该算法辨识棱镜摄谱仪的定标多项式,数值计算结果表明:采用改进的算法,非常显著地降低了求解定标多项式系数方程组的系数矩阵的条件数,定标多项式能更精确地反映谱平面坐标和谱线波长的定量关系。     

一阶可变号非线性奇异初值问题

获得了一类一阶可变号非线性奇异初值问题的新结果。     

便携式潮汐观测仪(PET)数据处理研究

介绍了用切比雪夫多项式和最小二乘相结合的数据拟合从重力固体潮观测的秒值提取分钟值和小时值的方法,该方法可以将错误数据自动剔除以得到可靠数据.将提取的数据应用于调和分析,效果良好.     

Estimation of pH optima and tolerances of diatoms in lake sediments by the methods of weighted averaging,least squares and maximum likelihood,and their use for the prediction of lake acidity

Ecological optima and tolerances with respect to autumn pH were estimated for 63 diatom taxa in 47 Finnish lakes. The methods used were weighted averaging (WA), least squares (LS) and maximum likelihood (ML), the two latter methods assuming the Gaussian response model.WA produces optimum estimates which are necessarily within the observed lake pH range, whereas there is no such restriction in ML and LS. When the most extreme estimates of ML and LS were excluded, a reasonably close agreement among the results of different estimation methods was observed. When the species with unrealistic optima were excluded, the tolerance estimates were also rather similar, although the ML estimates were systematically greater.The parameter estimates were used to predict the autumn pH of 34 other lakes by weighted averaging. The ML and LS estimates including the extreme optima produced inferior predictions. A good prediction was obtained, however, when prediction with these estimates was additionally scaled with inverse squared tolerances, or when the extreme values were removed (censored). Tolerance downweighting was perhaps more efficient, and when it was used, no additional improvement was gained by censoring. The WA estimates produced good predictions without any manipulations, but these predictions tended to be biased towards the centroid of the observed range of pH values.At best, the average bias in prediction, as measured by mean difference between predicted and observed pH, was 0.082 pH units and the standard deviation of the differences, measuring the average random prediction error, was 0.256 pH units.     

COMPARISON OF MEASUREMENT METHODS BASED ON A MODEL FOR THE ERROR STRUCTURE

Comparison of methods is a technique often used for investigation of systematic errors of measurementmethods.As concerns the design and analysis of such comparisons,much variety of opinion and practiceexists.In one approach a few specimens are measured several times by different operators in differentlaboratories(reproducibility conditions)and in another approach several specimens are measured on oneor a few occasions by one operator in the same laboratory(repeatability conditions).In this paper amodel for the error structure of measurements is formulated and it is emphasized that one has todistinguish between two types of systematic errors:the first type depends only on the level of themeasured quantity and the second type is specific for the separate specimens.On the basis of this modelthe information which can be obtained from the different designs of method comparisons is discussed.A new approach for the analysis of method comparisons with many specimens is also proposed.     

腾冲火山区地表垂直形变分析

对腾冲火山区1998～2000年的3期垂直形变资料进行了分析，进而利用相关资料得出与计算有关的参数，再用多元Mogi模型反演了岩浆房的位置和大小，所得出的结果与地震层析反演结果基本相似。分析反演结果，认为火山区可能存在多个岩浆房，并有岩脉相通。     

一种估计观测资料动态误差的方法

给出一种较好的观测资料动态误差估计的方法：单圈改进法，该方法从轨道理论出发，有明确的物理背景，避免了最小二乘拟合阶数和Vondrak平滑法平滑因子不确定性，较为准确地估计了观测资料的动态误差．另外该方法能够反映观测资料的不正常的跳动，对准确地评估观测仪器的性能，进一步改进观测仪器是有益处的．     

Meixner functions for derivation of the unit hydrograph

The Meixner functions are utilized to relate the effective rainfall, the direct runoff and the unit hydrograph through linkage equations. The linkage equations are then employed to derive the unit hydrograph for given rainfall-runoff data on a small agricultural watershed. These functions are tested with regard to their ability to reproduce and predict the direct runoff hydrograph. The Meixner functions are found to be an effective analytical tool for hydrograph synthesis. Further, they compare well with the least squares and linear programming methods of the unit hydrograph derivation.     

A least-squares method for determining the best-fit point maximum, great circle, and small circle to nondirectional orientation data

Given a set of nondirectional orientation data (fold axes, lineations, dip and dip direction of bedding, universal stage readings of crystallographic axes, etc.),the best-fit line (point maximum),plane (great circle),or cone (small circle)can be determined by minimizing the sum of the squares of the angular residuals using a simplex convergence technique. Stereoplots of the angular deviation over the complete lower hemisphere for these distributions may also be generated when consideration of the constraint on the best-fit position is important; for example in comparing different data sets of the same structural element. The routines are available as a FORTRAN coded computer program.     

INFLUENCE OF SERIES OF SQUARE GRIDS ON FRACTAL DIMENSIONS—A Case Study of Mountains of China＇s Mainland

MANDELBROT enunciated the uncertainty of the length of a coastline in his paper “How long is the coastline of Britain?” published in Science in 1967. The fractal concept was presented for the first time in that paper and has been applied to many fields ever since. Although fractal dimensions of lots of phenomena were calculated by the box-counting method, the quantitative influence of series of square grids on them is ignored. The issue is systematically discussed as a case study of the mountains of China‘s Mainland in this paper. And some significant conclusions are drawn as follows: 1) Although the fractal character objectively exists in the mountains of China‘s Mainland, and it does not vary with the changes of series of square grids, the fractal dimensions of the mountains of China‘s Mainland are different with these changes. 2) The fractal dimensions of the mountains of China‘s Mainlandvary with the average lengths of sides of series of square grids. The fractal dimension of the mountains of China‘s Mainland is the function of the average length of side of square grid. They conform to the formula D=f(r) (where D is the fractal dimension, and r is the average length of side of square grid). 3) Different dots of data collection can affect the fractal dimension of the mountains of China‘s Mainland. 4) The same range of length of side of square grid and dots of data collection can ensure the comparison of fractal dimensions of the mountains of China‘ s Mainland. The research is helpful to get the more understanding of fractal and fractal dimension, and ensure that the fractal studies would be scientific.