多元统计学方法在光度分析中同时测定多组份体系应用的研究

本论文通过对计算方法的筛选，把目前被认为是最有前途的多元统计学方法－－主组份回归法（PCR）和偏最小二乘法（PLS）以及人们使用较多的CPA矩阵法固较为成熟的，且普遍使用的光度分析有机地结合在一起，对多组份混合体系进行了同时测定的应用研究。并详细阐述了多元线性回归方法（MLR）、PLS、PCR方法的基本数学原理，继而又以运行速度较快的FORTRAN语言分别编制了CPA矩阵法，PCR法，PLS法的计算机程序，实现了对光谱数据矩阵和校准浓度矩阵的计算机全处理过程，获得了预期的效果。经过它们处理计算的几个多组份混合体系的同时测定，也都取得了满意的结果。本文还通过对CPA矩阵法，PCR法和PLS法的计算测定的比较，归纳总结了它们各自的优缺点，并在校准样品的系列统计设计。以交叉证实法（Cross-Validation)确定最佳校准模型的因子数，不相容因子（DF）判定检查结果的可靠性等方面都作了较系统的有益探索，并提出了些新颖的观点和看法，证明了其具有广阔的应用前景。即使对有交互作用较强的药物样品的定量分析，仍取得了较满意的结果。本论文共作了如下四方面的探讨。1.CPA矩阵法在光度分析中进行多组份体系同时测定的研究。2.偏最小二乘法（PLS）在分光光度定量分析中的应用。它是以因子分析为基础的多元统计学方法。3.主组份回归法（PCR）同时计算测定钨、钼、钒。它是因子分析（FA）和MLR相结合的产物。故兼容了FA和多元线性回归法中的经典最小二乘法（CLS）和逆最小二法（ILS）的优点。4.多元统计学方法在光度分析中应用的研究。本文将较为优异的计算方法，PCR和PLS分别进行了多方面的分析测定研究。总之，PCR和PLS法都是因子分析（FA）和多元线性回归法（MLR）相结合的产物。在目前的计算方法中，被认为是最有前途的多元统计学方法。

区域水土流失研究中降雨量空间插值方法选取

在区域水土流失模型研究中,空间插值可提供每个计算栅格的气象要素资料。考虑到研究区域降雨与高程相关性很弱,不宜采用梯度距离反比法(GIDS),故采用距离反比法(IDW)和普通克里格法(Kriging),对延安示范区及其周围共50个站点2000—2003年的5—10月逐月降雨量进行插值。交叉验证结果表明:对2种插值方法,二者经过对数变换后平均相对误差(MRE)为8.30%和7.67%,分别比原始数据插值后的MRE下降了23.17%和23.50%,说明插值精度得到了提升,对研究区域某一年逐月降水的插值Kriging方法比IDW方法更加精确。

Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: Accuracy and uncertainty analysis

Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal concentrations at unsampled sites. The performances of interpolation methods (inverse distance weighting, local polynomial, ordinary kriging and radial basis functions) were assessed and compared using the root mean square error for cross validation. The results indicated that all interpolation methods provided a high prediction accuracy of the mean concentration of soil heavy metals. However, the classic method based on percentages of polluted samples, gave a pollution area 23.54-41.92% larger than that estimated by interpolation methods. The difference in contaminated area estimation among the four methods reached 6.14%. According to the interpolation results, the spatial uncertainty of polluted areas was mainly located in three types of region: (a) the local maxima concentration region surrounded by low concentration (clean) sites, (b) the local minima concentration region surrounded with highly polluted samples; and (c) the boundaries of the contaminated areas. (C) 2010 Elsevier Ltd. All rights reserved.

Study on QSPR of alcohols with a novel edge connectivity index F-m

A novel edge degree f(i) for heteroatom and multiple bonds in molecular graph is derived on the basis of the edge degree delta(e(r)). A novel edge connectivity index F-m is introduced. The multiple linear regression by using the edge connectivity index F-m and alcohol-type parameter delta, alcohol-distance parameter L can provide high-quality QSPR models for the normal boiling points (BPs), molar volumes (MVs), molar refraction (MRs), water solubility(log(1/S)) and octanol/water partition (logP) of alcohols with up to 17 non-hydrogen atoms. The results imply that these physical properties may be expressed as a liner combination of the edge connectivity index and alcohol-type parameter, 6, alcohol-distance parameter, L. For the models of the five properties, the correlation coefficient r and the standard errors are 0.9969,3.022; 0.9993, 1.504; 0.9992, 0.446; 0.9924,0.129 and 0.9973,0.123 for BPs, MVs, MRs, log(1/S) and logP, respectively. The cross-validation by using the leave-one-out method demonstrates the models to be highly reliable from the point of view of statistics.

电阻率测井反演方法应用研究

Formation resistivity is one of the most important parameters to be evaluated in the evaluation of reservoir. In order to acquire the true value of virginal formation, various types of resistivity logging tools have been developed. However, with the increment of the proved reserves, the thickness of interest pay zone is becoming thinner and thinner, especially in the terrestrial deposit oilfield, so that electrical logging tools, limited by the contradictory requirements of resolution and investigation depth of this kinds of tools, can not provide the true value of the formation resistivity. Therefore, resitivity inversion techniques have been popular in the determination of true formation resistivity based on the improving logging data from new tools. In geophysical inverse problems, non-unique solution is inevitable due to the noisy data and deficient measurement information. I address this problem in my dissertation from three aspects, data acquisition, data processing/inversion and applications of the results/ uncertainty evaluation of the non-unique solution. Some other problems in the traditional inversion methods such as slowness speed of the convergence and the initial-correlation results. Firstly, I deal with the uncertainties in the data to be processed. The combination of micro-spherically focused log (MSFL) and dual laterolog(DLL) is the standard program to determine formation resistivity. During the inversion, the readings of MSFL are regarded as the resistivity of invasion zone of the formation after being corrected. However, the errors can be as large as 30 percent due to mud cake influence even if the rugose borehole effects on the readings of MSFL can be ignored. Furthermore, there still are argues about whether the two logs can be quantitatively used to determine formation resisitivities due to the different measurement principles. Thus, anew type of laterolog tool is designed theoretically. The new tool can provide three curves with different investigation depths and the nearly same resolution. The resolution is about 0.4meter. Secondly, because the popular iterative inversion method based on the least-square estimation can not solve problems more than two parameters simultaneously and the new laterolog logging tool is not applied to practice, my work is focused on two parameters inversion (radius of the invasion and the resistivty of virgin information ) of traditional dual laterolog logging data. An unequal weighted damp factors- revised method is developed to instead of the parameter-revised techniques used in the traditional inversion method. In this new method, the parameter is revised not only dependency on the damp its self but also dependency on the difference between the measurement data and the fitting data in different layers. At least 2 iterative numbers are reduced than the older method, the computation cost of inversion is reduced. The damp least-squares inversion method is the realization of Tikhonov's tradeoff theory on the smooth solution and stability of inversion process. This method is realized through linearity of non-linear inversion problem which must lead to the dependency of solution on the initial value of parameters. Thus, severe debates on efficiency of this kinds of methods are getting popular with the developments of non-linear processing methods. The artificial neural net method is proposed in this dissertation. The database of tool's response to formation parameters is built through the modeling of the laterolog tool and then is used to training the neural nets. A unit model is put forward to simplify the dada space and an additional physical limitation is applied to optimize the net after the cross-validation method is done. Results show that the neural net inversion method could replace the traditional inversion method in a single formation and can be used a method to determine the initial value of the traditional method. No matter what method is developed, the non-uniqueness and uncertainties of the solution could be inevitable. Thus, it is wise to evaluate the non-uniqueness and uncertainties of the solution in the application of inversion results. Bayes theorem provides a way to solve such problems. This method is illustrately discussed in a single formation and achieve plausible results. In the end, the traditional least squares inversion method is used to process raw logging data, the calculated oil saturation increased 20 percent than that not be proceed compared to core analysis.