回归模型在辐射环境监测中的应用

提出了回归分析前作变量变换的依据，并认为变量的概率分布相同时可不作变量变换；应用江苏省土壤中镭和钍的数据建立的数学模型，对该省污染预测、重复调查本底具有现实意义。     

链烷烃的热力学性质与分子拓扑指数的关系

定义了一种新的连接性指数^1Y=Σk1/m^2 n^2,研究了链烷烃的标准生成焓、标准熵、标准生成吉布斯自由能等三个热力学性质与碳原子个数N，^1Y之间的定量关系，相关系数为优，其计算值与实验值较为接近，对未参与回归的正癸烷的60个异构体的三个热力学性质进行了计算，计算值与实验值较一致。     

区域趋势控制协变量回归分析效果评估方法研究

本文根据区域趋势控制和气象－物理协变量相关设计了三套非随机化人工增雨作业效果评估方案，个例作用区域趋势对比双比分析评估方案，区域趋势相关回归分析评估方案和气象－物理协变量多元回归分析评估方案，对河南省实例评估计算表明，利用物理协变量作为控制因子，可以提高作业区自然水量估计值的准确度，从而能提高随机化作业的效果评估效率。     

Application of GIS Processing Techniques for Producing Mineral Prospectivity Maps—A Case Study: Mesothermal Au in the Swayze Greenstone Belt,Ontario, Canada

A Geographic Information System (GIS) is used to prepare and process digital geoscience data in a variety of ways for producing gold prospectivity maps of the Swayze greenstone belt, Ontario, Canada. Data used to produce these maps include geologic, geochemical, geophysical, and remotely sensed (Landsat). A number of modeling methods are used and are grouped into data-driven (weights of evidence, logistic regression) and knowledge-driven (index and Boolean overlay) methods. The weights of evidence (WofE) technique compares the spatial association of known gold prospects with various indicators (evidence maps) of gold mineralization, to derive a set of weights used to produce the final gold prospectivity map. Logistic regression derives statistical information from evidence maps over each known gold prospect and the coefficients derived from regression analysis are used to weight each evidence map. The gold prospectivity map produced from the index overlay process uses a weighting scheme that is derived from input by the geologist, whereas the Boolean method uses equally weighted binary evidence maps.The resultant gold prospectivity maps are somewhat different in this study as the data comprising the evidence maps were processed purposely differently for each modeling method. Several areas of high gold potential, some of which are coincident with known gold prospects, are evident on the gold prospectivity maps produced using all modeling methods. The majority of these occur in mafic rocks within high strain zones, which is typical of many Archean greenstone belts.     

Maximum likelihood environmental calibration and the compute program WACALIB a correction

A recently discovered error in the part of the computer program WACALIB that implements maximum likelihood (ML) calibration has been discovered and corrected. The new version of WACALIB has been re-run with all the data-sets from which results based on the earlier version of WACALIB had been published. The new results suggest that ML regression and calibration perform as well or even better than weighted averaging (WA), at least when judged by the apparent root mean squared error. Further work involving cross-validation is required to evaluate more fully the relative performance of WA and ML approaches.     

Thematic Map Analysis Using Multiple Regression

Thematic maps can be analyzed by multiple regression for (1) forward prediction where a younger geological structural map is written as a least-squares function of older maps for information on historical perspectives or (2) by backward prediction where an older map is regressed stepwise on a series of younger ones to aid in prospecting. The technique was evaluated by a series of structure maps on different geological horizons from the U.S. Midcontinent (Kansas) where the forward prediction proved more effective than backward. In forward prediction, the first map entered into a multiple regression is invariably the immediately underlying one as expected. On the other hand, the first map in a backward prediction is not necessarily related to stratigraphy which limits the utility of the technique for prospecting.     

山地降水垂直分布三参数高斯模式及其应用

针对蒋忠信山地降水高斯模式计算中的问题,提出三参数高斯模式及其非线性回归计算方法,将其应用于我国部分山地降水中,效果较好。     

本溪市区剪切波速分布的初步研究

本文利用检层法、表面波法实测的波速资料。通过对实测数据的处理和回归分析,求出了本溪市区不同岩土波速与埋深的回归关系。同时收集了市区已有的钻孔资料,经分析计算,给出了本溪市区平均剪切波速的分布。     

回归方程在岩矿分析质量监控方面的应用

依据在特定的地质环境及较为均一的地质体中,一些元素具有共生组合的现象,提出用回归分析的方法为质量监控方式,取得了满意的效果。