格运算的扩张定理与落影函数定理

讨论了格上可测结构的封闭性以及此结构上落影函数的有关问题。指出并证明了逐次扩张与同时扩张的充要条件 ,以及落影函数与模糊集的关系     

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。     

Generating soil thickness maps by means of geomorphological-empirical approach and random forest algorithm in Wanzhou County,Three Gorges Reservoir

Soil thickness, intended as depth to bedrock, is a key input parameter for many environmental models. Nevertheless, it is often difficult to obtain a reliable spatially exhaustive soil thickness map in wide-area applications, and existing prediction models have been extensively applied only to test sites with shallow soil depths. This study addresses this limitation by showing the results of an application to a section of Wanzhou County (Three Gorges Reservoir Area, China), where soil thickness varies from 0 to ～40 m. Two different approaches were used to derive soil thickness maps: a modified version of the geomorphologically indexed soil thickness (GIST) model, purposely customized to better account for the peculiar setting of the test site, and a regression performed with a machine learning algorithm, i.e., the random forest, combined with the geomorphological parameters of GIST (GIST-RF). Additionally, the errors of the two models were quantified, and validation with geophysical data was carried out. The results showed that the GIST model could not fully contend with the high spatial variability of soil thickness in the study area: the mean absolute error was 10.68 m with the root-mean-square error (RMSE) of 12.61 m, and the frequency distribution residuals showed a tendency toward underestimation. In contrast, GIST-RF returned a better performance with the mean absolute error of 3.52 m and RMSE of 4.56 m. The derived soil thickness map could be considered a critical fundamental input parameter for further analyses.     

Effect of 2D spatial variability on slope reliability: A simplified FORM analysis

To meet the high demand for reliability based design of slopes, we present in this paper a simplified HLRF(Hasofere Linde Rackwitze Fiessler) iterative algorithm for first-order reliability method(FORM). It is simply formulated in x-space and requires neither transformation of correlated random variables nor optimization tools. The solution can be easily improved by iteratively adjusting the step length. The algorithm is particularly useful to practicing engineers for geotechnical reliability analysis where standalone(deterministic) numerical packages are used. Based on the proposed algorithm and through direct perturbation analysis of random variables, we conducted a case study of earth slope reliability with complete consideration of soil uncertainty and spatial variability.     

Probabilistic stability analyses of undrained slopes by 3D random fields and finite element methods

A long slope consisting of spatially random soils is a common geographical feature. This paper examined the necessity of three-dimensional(3 D) analysis when dealing with slope with full randomness in soil properties. Although 3 D random finite element analysis can well reflect the spatial variability of soil properties, it is often time-consuming for probabilistic stability analysis. For this reason, we also examined the least advantageous(or most pessimistic) cross-section of the studied slope. The concept of"most pessimistic" refers to the minimal cross-sectional average of undrained shear strength. The selection of the most pessimistic section is achievable by simulating the undrained shear strength as a 3 D random field. Random finite element analysis results suggest that two-dimensional(2 D) plane strain analysis based the most pessimistic cross-section generally provides a more conservative result than the corresponding full 3 D analysis. The level of conservativeness is around 15% on average. This result may have engineering implications for slope design where computationally tractable 2 D analyses based on the procedure proposed in this study could ensure conservative results.     

随机森林模型预测岩溶区酸性煤矿井水锰污染

酸性煤矿井水严重威胁地下水的水质。如何更有效对受影响区域的地下水源进行动态监测是当前的一个关键问题。采用随机森林中的回归模型,利用自变量(采空区水位、岩溶水位、pH值、泉水流量、电导率)和因变量(污染离子浓度)的相关性,建立回归模型;使用测试数据进行误差分析,结果证明模型准度较高,所得预测值具有参考价值;得出各自变量对因变量影响的重要程度,分析结果与实际情况相符合。试验表明,随机森林回归模型在酸性煤矿井水污染预测方面具有适用性,可作为辅助手段监测水质污染情况,对今后工作有一定的指导意义和经济价值。     

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.     

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.     

宁夏及邻区地震活动能量场时空变化特征

运用随机函数理论,将宁夏及邻区地震活动能量场看作时间和空间的随机函数,用自然正交函数展开方法,系统研究宁夏及邻区主要典型能量场的时间权重系数变化曲线以及典型能量场的空间等值线图。结果发现,目标曲线较大幅度的升、降变化预示了可能发生中强地震的时间段,而等值线图的高值变化（危险区）对应了可能发生中强地震的区域。