基于环境因子和邻近信息的土壤属性空间分布预测

为探索乡镇尺度上土壤属性空间分布预测的最佳方法,以江西省万年县齐埠镇为例,借助四方位搜索法、地统计学和遥感影像分析技术提取环境因子（地形因子和植被覆盖指数）和邻近信息[w（有机质）与w（速效钾）],构建OK法（普通克里金法）、RK1法（仅基于环境因子的回归克里金法）以及RK2法（基于环境因子和邻近信息的回归克里金法）对齐埠镇耕地表层（0~20 cm）土壤w（有机质）、w（速效钾）空间分布进行预测.结果表明:齐埠镇土壤w（有机质）平均值为35.03 g/kg,w（速效钾）平均值为96.73 mg/kg,均为中等空间变异性.对62个样点进行建模,16个测试样点进行独立验证的误差分析表明,RK2法对土壤w（有机质）、w（速效钾）预测结果的均方根误差、平均绝对误差和平均相对误差较OK法分别降低了18.05%、18.01%、21.77%和7.25%、9.49%、9.84%;较RK1法分别降低了22.48%、20.91%、22.02%和9.27%、12.61%、13.52%.研究显示,RK2法明显提高了土壤w（有机质）、w（速效钾）空间分布模拟精度,并且存在改进和提高的空间.      

石羊河流域1959年至2008年风速变化特征分析

利用线性拟合、Mann—Kendall方法、小波分析对石羊河流域五个测站空间平均的近50年来的逐日风速资料进行了倾向、周期、突变等特性分析。研究结果表明：1959年至2008年间,整个石羊河流域风速呈减小趋势,变化率约为-0．004m／（s．a）．而上游风速呈现明显的上升趋势。四个季节中冬季风速降低速度最大,而夏季风速呈现上升趋势。风速的长期变化还具有一定的突变性,年平均风速在1988年出现了由高到低的突变,表明风速开始下降。复值Morlet小波分析的结果显示,风速变化存在6a、13a、19a、25a四个峰值。其中19a的时间尺度为第一主周期。     

便携β射线法手工监测PM_(2.5)的可行性研究

提出利用自动射线原理结合重量法的简捷便携特点的便携射线仪手工监测PM2.5的思路,平行比对了便携射线法和手工重量法所测60组PM2.5浓度的监测结果,采用线性回归及T检验、F检验等理论分析了两者数据结果间的有效性和可比性。结果表明,便携式射线仪监测结果与重量法监测结果之间有效可比且得到了两者间的线性回归方程;此外进行了20组数据的实样验证,换算值和真值之间相对误差在8%以内,因而确定了便携射线仪手工监测PM2.5的可行性。     

体育馆出口疏散能力的实验研究

为研究出口单位流量与人流时间之间的关系,以某体育馆为例,进行对某一出口常态下的人流观测实验.通过理论计算和建立Cubic回归模型对采集数据进行了统计分析.发现:单位出口流量最大值为2人/(m·s),稳定值为0.8-1.2人/(m·s),最小值为0.2人/(m·s).出口单位流量是人流时间的三次函数.研究结果表明:出口单位流量是随着时间的变化而变化,不是一个定值,而且单位出口流量稳定值分布在初期.本文对性能化防火设计有一定的参考价值.     

A statistical analysis of the carbon dioxide capture process

Post combustion carbon dioxide (CO₂) capture is one of the most commonly adopted technologies for reducing industrial CO₂ emissions, which is now an important goal given the widespread concern over global warming. Research on amine-based CO₂ capture has mainly focused on improving effectiveness and efficiency of the CO₂ capture process. Our research work focuses on studying the relationships among the significant parameters influencing CO₂ production because an enhanced understanding of the intricate relationships among the parameters involved in the process is critical for improving efficiency of the CO₂ capture process. This paper presents a statistical study that explores the relationships among parameters involved in the amine-based post combustion CO₂ capture process at the International Centre for CO₂ Capture (ITC) located in Regina, Saskatchewan of Canada. A multiple regression technique has been applied for analysis of data collected at the CO₂ capture pilot plant at ITC. The parameters have been carefully selected to avoid issues of multicollinearity, and four mathematical models among the key parameters identified have been developed. The models have been tested, and accuracy of the models is found to be satisfactory. The models developed in this study describe part of the CO₂ capture process and can help to predict performance of the CO₂ capture process at ITC under different conditions. Some results from a preliminary validation process will also be presented.     

Statistical Analysis of Air Pollutants and Meteorological Parameters in Afyon, Turkey

In this study, the relation between sulfur dioxide (SO₂) and particulate matter (PM) concentrations periodically measured in the city of Afyon’s atmosphere with meteorological factors such as precipitation, humidity, temperature, wind velocity, and inversion were investigated. The mean values of SO₂ and PM concentrations measured during the winter months of October–March 1990–1999 were correlated with the meteorological parameters of the same period. Simple and multiple linear regression analysis were utilized to evaluate the contribution of meteorological variables. The statistical results show that the pollutants, i.e., SO₂ and PM are dependent upon humidity, temperature, and inversion at the 1% significance level; while the dependence of both pollutants with temperature is negative when those of humidity and inversion are positive. Two models in which temperature and inversion are dependent with multiple variables are recommended for predicting the contribution of meteorological parameters on SO₂ and PM. In addition, the relationship between humidity, temperature, and inversion with pollutants is also determined using nonlinear (polynomial) models.     

桂西北河池地区耕地变化及其驱动力Logistic回归分析

桂西北河池地区土地退化严重，耕地少，区域农业发展受限。基于TM遥感图像、DEM等空间数据并结合社会经济统计数据，利用空间分析方法及Logistic回归分析模型，定量分析了1952～2006年桂西北河池地区11个县耕地的时空动态变化规律及其驱动机制。研究结果表明：1952～2006年河池地区耕地总量的变化经历了迅速增加-波动变化-迅速减少-缓慢减少的过程，空间上变化率不均衡，且近20多a间西部地区耕地减少迅速，其变化体现了国家政策的主导驱动作用；根据回归结果提取出7类影响耕地分布的主要解释变量，其中海拔和人口分布为耕地空间分布格局分异的关键影响因素，其次是坡度Ⅰ(0°～5°)、GDP、至主要公路距离、至主要河流距离和至主要城镇距离；不同县之间耕地变化驱动力的解释变量存在差异，且各县耕地分布概率对于海拔、坡度Ⅰ(0°～5°)、GDP这3类解释变量较敏感，而其他解释变量敏感程度较低；东部地区耕地分布的概率更大.     

Evaluating the effects of spatial monitoring policy on groundwater quality portrayal

What size sample is sufficient for spatially sampling ambient groundwater quality? Water quality data are only as spatially accurate as the geographic sampling strategies used to collect them. This research used sequential sampling and regression analysis to evaluate groundwater quality spatial sampling policy changes proposed by California's Department of Water Resources. Iterative or sequential sampling of a hypothetical groundwater basin's water quality produced data sets from sample sizes ranging from 2.8% to 95% coverage of available point sample sites. Contour maps based on these sample data sets were compared to an original (control), mapped hypothetical data set, to determine at which point map information content and pattern portrayal are not improved by increasing sample sizes. Comparing series of contour maps of ground water quality concentration is a common means of evaluating the geographic extent of groundwater quality change. Comparisons included visual inspection of contout maps and statistical tests on digital versions of these map files, including correlation and regression products. This research demonstrated that, down to about 15% sample site coverage, there is no difference between contour maps produced from the different sampling strategies and the contout map of the original data set.     

关于铁路行车事故预测的应用研究

本文论述了事故预测对铁路行车安全的重要性,并应用灰色预测模型和概率回归估计法模型研制了预测软件,进行铁路行车事故的宏观及微观预测,为采取有针对性的防范措施提供一个可靠信息。     

两种定性天气预报模型的对比分析

以南京１９６５～１９９４ 年４ 月平均气温作为预报量, 选取前期５００ ｈ Ｐａ 月平均高度场相关因子, 分别建立了事件概率回归预报模型和神经网络预报模型。通过对比分析发现, 在同等条件下,由于神经网络方法能更好地反映预报量与预报因子间的非线性关系, 并能有效避免采用事件概率回归方法预报建模时, 对预报因子分级造成信息损失的缺点。因此, 其拟合和预报效果明显优于传统的概率回归预报方法