幂函数对建筑物沉降的回归分析

通过实例推导幂函数对建筑物沉降进行回归分析，并且得出较为精确的结果，同时也说明在选择回归函数的时候，还会受到很多条件影响。     

利用气象要素计算五道梁地区土壤热流量的试验

根据五道梁地区1994—1997年的热流板测量土壤热流值,初步分析了该地区土壤热流随时间的变化特征。利用1994—1996年的月平均资料分别分析了总辐射、地表温度、地表温度和80 cm深度温度差和2 cm、10 cm深度的土壤热流的相关性,并建立了相应的回归方程;利用得到的回归方程对1997年的土壤热流作计算检验,就月平均资料来说,用总辐射和地温差来计算浅层土壤热流结果是比较可靠的。     

Singular value decomposition and cluster analysis as regression diagnostics tools for geodetic applications

It is well known that high-leverage observations significantly affect the estimation of parameters. In geodetic literature, mainly redundancy numbers are used for the detection of single high-leverage observations or of single redundant observations. In this paper a further objective method for the detection of groups of important and less important (and thus redundant) observations is developed. In addition, the parameters which are predominantly affected by these groups of observations are identified. This method thus complements other diagnostics tools, such as, e.g., multiple row diagnostics methods as described in statistical literature (see, e.g., Belsley et al. in Regression diagnostics: identifying influential data and sources of collinearity. Wiley, New York, 1980). The method proposed in this paper is based on geometric aspects of adjustment theory and uses the singular value decomposition of the design matrix of an adjustment problem together with cluster analysis methods for regression diagnostics. It can be applied to any geodetic adjustment problem and can be used for the detection of (groups of) observations that significantly affect the estimated parameters or that are of negligible impact. One of the advantages of the proposed method is the improvement of the reliability of observation plans and thus the reduction of the impact of individual observations (and outliers) on the estimated parameters. This is of particular importance for the very long baseline interferometry technique which serves as an application example of the regression diagnostics tool.     

使用Python函数式编程进行空间回归分析

针对使用传统的编程方式进行空间回归分析过于繁杂的问题,本文提出将Python函数式编程引入空间回归分析方法,分析和探讨脚本语言＋函数式编程方式在GIS数据分析中的推广应用前景。编程实践证明,采用Python函数式编程,结合既有的开源软件包,可以有效提高编程效率,减少代码量,将实践人员的注意力集中在问题本身。     

经济预测模型在土地规划中的应用与分析

主要介绍土地规划时需用到的几种预测模型 ,具体阐述了几种模型的原理 ,并以抚州地区的总人口历史数据为例 ,进行实际的预测与分析 ,从而总结各种模型的优缺点 ,选择最合适的土地规划预测模型。     

Allocycles and Autocycles in the Upper Part of the Limestone Coal Group (Pendleian E1) in the Glasgow–Stirling Region of the Midland Valley of Scotland

The upper part of the Limestone Coal Group (Pendleian E₁), between the major marine transgressions of the Black Metals and the Index Limestone, represents an early example of ‘coal measures’ facies. It comprises a distal and a proximal facies association. The distal facies association, which was subject to relatively strong marine influences and included both deltaic and fluvial elements, is characterized by a regular ‘layer-cake’ succession with laterally-persistent lithological members. By contrast, the proximal association, which was more subject to fluvial influences and is typified by the variable Bannockburn Main Complex, is characterized by abrupt lateral changes in lithofacies. The distal facies association is dominant in the west of the Kilsyth Trough, but proximal facies intercalations increase eastwards, so that they constitute a fairly high proportion of the succession in the Kincardine Basin, particularly in areas of locally-increased tectonic subsidence that were frequently occupied by major channel belts. Some of the sheet sandstones within the distal association have a lower, upward-coarsening portion succeeded by a coarser-grained, erosive-based, upward-fining portion. The resulting ‘two-storey’ profile may reflect deltaic sand bodies having been suceeded by fluvial sand bodies, following a general fall in base level. Linear regression lines showing the relationship between the number of horizons colonized by vegetation and net subsidence, suggest that local autocyclic, tectonosedimentary processes, such as delta switching, channel migration, and avulsion, were superimposed upon a widespread allocyclic, probably glacial-eustatic, process. The former processes were most effective within the proximal facies association and in the Kincardine Basin and the latter in the distal association and the Kilsyth Trough.     

南黄海表层沉积物天然湿容重和含水量的分布及其与粒度之间的关系

本文论述了南黄海表层沉积物天然湿容重和含水量的分布,并利用回归分析的方法讨论了容重和含水量与粒度之间的关系。结果表明,容重和含水量与粘土粒级相关性最好,容重与粘土粒级含量(相似文献   

青藏高原及周缘地壳浅层构造应力场量值特征分析

以"中国大陆地壳应力环境基础数据库"中的实测地应力数据为基础,合理筛选出地理空间范围为21°N—40°N,73°N —110°N的近2000条数据,深度范围0~2 km.通过将研究区内实测地应力扣除重力影响,并考虑数据样本数量沿深度分布不均匀的问题,分析构造应力场的作用.重力影响的扣除采用海姆假说与金尼克假说两种模式估算其下限与上限,给出了青藏高原及周缘及青藏地块、南北地震带北、中、南段上构造应力和构造差应力随深度分布的特征和量值范围.结果显示：（1）青藏高原及周缘地区最大水平应力σH、最小水平应力σh随深度D呈线性增加：σH=22.115D+5.761、σh= 14.893D+3.269;最大水平构造应力σT、最小水平构造应力σt的量值估算范围分别为4.609 < σT < 15.522D+4.609、3.121 < σt < 6.366D+3.121（D >0）;构造差应力σT-σt=7.222D+2.492,地表值（D=0 km）为2.5 MPa左右,随深度增加以7.2 MPa·km-1的梯度增大;（2）在测量深度范围内,青藏地块、南北地震带北、中、南段研究区σT、σt、σT-σt随埋深均呈线性增大;D=1 km时,各地块σT的统计回归值中最大为30.1 MPa,最小为17.6 MPa,量值由大到小排序依次为：青藏地块、南北带北段、南北带中段、南北带南段;D=1 km时,各地块σT-σt的统计回归值中最大为15.8 MPa,最小为8.9 MPa,量值由大到小排序依次为：青藏地块、南北带北段、南北带中段和南北带南段.总体表现为青藏地块强、南北带较弱的基本特征.（3）与南北带相比较,青藏地块地壳在从南向北的挤压作用下呈现出明显的"浅弱深强"特点.     

重庆及邻区震后烈度分布评估模型构建

选取重庆及邻区作为研究区域,将典型历史地震震例的等震线图数字化,通过回归分析分别构建了基于烈度衰减关系的烈度分布评估模型、基于等震线长短轴半径的“王景来”烈度分布评估模型和基于面积的烈度分布评估模型.最后利用算例验证了上述三种模型的适用性.震后烈度分布评估模型对于震后灾害损失评估有重要的意义.     

Investigating Correlations and Variations of Air Pollutant Concentrations under Conditions of Rapid Industrialization – Kocaeli (1987–2009)

In this study, it was aimed to characterize temporal variations of air pollutants for determining contribution to pollution episodes and to obtain correlations between these pollutants. With this aim we used data analysis for measured sulfur dioxide (SO₂), particulate matter (PM, black fume and PM10), nitrogen oxides (NO_x), ozone (O₃), carbon monoxide (CO), methane (CH₄), and non‐methane hydrocarbons (NMHC) recorded in Kocaeli, one of the most industrilizated cities of Turkey. Pollutant concentrations were the results of continuous and semi‐automatic measurements. Semi‐automatic measurements of SO₂ and PM (black fume) were enclosing period from 1987 to 2008 whereas continuous monitoring of all pollutants included years of 2007–2009. In the first stage of the study daily, monthly, annual, and seasonal variations of pollution were researched. Annual average concentrations were compared with limits set by Air Quality Protection Regulation (AQPR), Air Quality Evaluation and Management Regulation (AQEMR), World Health Organization (WHO), European Union (EU), and National Ambient Air Quality Standards (USEPA). In the following stage relationships between pollutants such as NO₂–O₃, NO_x–CO, NO_x–NMHC, and NO_x–SO₂ were investigated and correlation coefficients were determined as 0.87, 0.56, 0.51, and 0.69, respectively. R² values of regression models developed from these correlations were 0.78, 0.56, 0.34, and 0.72, respectively. Vehicle density of the traffic was evaluated with NO_x–O₃ emissions and decrease was seen in NO_x emissions due to decreasing vehicle density at weekends whereas O₃ concentrations increased. These correlations enable prediction of the parameters that cannot be measured which is important for providing improvement in early warning systems.