高阶模糊区域的交叉拓扑关系形式化研究

目的 基于区间Ⅱ－型模糊区域模型,讨论了区间Ⅱ－型模糊区域的结构,通过对传统的n-交模型进行扩展,提出了区间Ⅱ－型模糊区域拓扑关系的n-交矩阵和各原子的计算方法,并提出了拓扑关系的形式化分析方法。通过计算区间Ⅱ－型模糊拓扑关系矩阵与8种基本拓扑关系矩阵的相似度并排序,确定其首要拓扑关系,结合拓扑关系距离确定其可能存在的次要拓扑关系。     

Transient analysis of wave propagation in non‐homogeneous elastic unbounded domains by using the scaled boundary finite‐element method

The scaled boundary finite‐element method has been developed for the dynamic analysis of unbounded domains. In this method only the boundary is discretized resulting in a reduction of the spatial dimension by one. Like the finite‐element method no fundamental solution is required. This paper extends the scaled boundary finite‐element method to simulate the transient response of non‐homogeneous unbounded domains with the elasticity modulus and mass density varying as power functions of spatial coordinates. To reduce the number of degrees of freedom and the computational cost, the technique of reduced set of base functions is applied. The scaled boundary finite‐element equation for an unbounded domain is reformulated in generalized coordinates. The resulting acceleration unit‐impulse response matrix is obtained and assembled with the equation of motion of standard finite elements. Numerical examples of non‐homogeneous isotropic and transversely isotropic unbounded domains demonstrate the accuracy of the scaled boundary finite‐element method. Copyright © 2006 John Wiley & Sons, Ltd.     

基于熵权的集对分析法在水资源可持续利用评价中的应用——以塔里木河三源流地区为例

以塔里木河三源流地区为研究对象,结合研究区2004-2007年统计年鉴资料,从社会经济、水资源和生态环境三方面构建水资源可持续利用评价指标体系,采用集对分析和熵权法,对研究区水资源可持续利用进行评价.结果表明:塔里木河三源流地区水资源开发利用已基本达到饱和,水资源可持续利用呈现弱不可持续状态,具体表现为和田地区(Ⅲ)阿克苏地区(Ⅲ)喀什地区(Ⅲ).基于评价结果提出了一些促进三源流地区水资源可持续利用的措施.     

集对分析在西安市地下水污染动态评价的应用

选取总固体、总硬度、硝酸盐、氯化物、氟化物、六价铬等六种主要污染物,利用集对分析的方法,将超标率、污染指数和超标面积指数综合起来,对 1985-2003 年西安建成区地下水进行了动态评价.该方法既克服了依靠某年监测值对地下水质的静态空间评价,又可将超标率、污染指数和超标面积综合起来,完成地下水水质的动态评价.     

低轨卫星通信系统星座设计与性能仿真

低轨卫星通信系统在通信领域发挥着越来越重要的作用。针对不同类型星座覆盖能力和星际链路建立条件存在的差异,设计了极轨道和倾斜圆轨道低轨卫星星座,利用STK验证了两种星座的覆盖能力和星际链路AER特性,利用NS2对两种星座卫星网络的时延、吞吐量和丢包率等性能指标进行了仿真,并对所得数据进行了对比分析,结果表明：在由32颗卫星（轨道高度1450 km ）构成的低轨星座中,极轨星座的全球覆盖能力、星际链路建立条件和卫星网络性能优于倾斜圆轨道星座,更适合于构建全球低轨卫星通信系统。     

乍得BS油藏沉积微相特征及对油气分布的控制作用

结合区域沉积背景,应用BS1-1取心井资料进行泥岩颜色、岩石组合、沉积结构、构造、粒度分布、沉积韵律等相标志分析,对BS油藏沉积微相特征进行了深入研究,分析了沉积微相对油气分布的控制作用。BS油藏PI油层组为扇三角洲前缘远端沉积,水下分流河道分布范围有限,仅在断层附近发育,河道前端受湖浪作用改造明显,前缘席状砂发育,偶见远砂坝,河道间微相不发育。沉积微相类型控制了储层类型及其展布方式和储集性能,沉积微相展布对油气分布具有明显的控制作用,水下分流河道生储盖组合良好,为油气有利富集相带。     

基于集对分析的洪水分类研究

为避免常规分类方法复杂的数学理论和繁琐的计算,提出了基于集对原理的洪水分类新方法——集对分析法(SPAM)。系统地给出了集对分析法的基本思路和计算步骤。建议方法概念清晰,结构简单,计算简洁,易操作,是一种有效的分类途径。以实测洪水过程为例,应用研究表明集对分析法的分类结果是可行的。     

粗糙集理论进行遥感图像监督分类的样本质量评价的研究

In the supervised classification process of remotely sensed imagery, the quantity of samples is one of the important factors affecting the accuracy of the image classification as well as the keys used to evaluate the image classification. In general, the samples are acquired on the basis of prior knowledge, experience and higher resolution images. With the same size of samples and the same sampling model, several sets of training sample data can be obtained. In such sets, which set reflects perfect spectral characteristics and ensure the accuracy of the classification can be known only after the accuracy of the classification has been assessed. So, before classification, it would be a meaningful research to measure and assess the quality of samples for guiding and optimizing the consequent classification process. Then, based on the rough set, a new measuring index for the sample quality is proposed. The experiment data is the Landsat TM imagery of the Chinese Yellow River Delta on August 8th, 1999. The experiment compares the Bhattacharrya distance matrices and purity index zl and △x based on rough set theory of 5 sample data and also analyzes its effect on sample quality.     

Reconstructing fluvial bar surfaces from compound cross‐strata and the interpretation of bar accretion direction in large river deposits

The interpretation of fluvial styles from the rock record is based for a significant part on the identification of different types of fluvial bars, characterized by the geometric relationship between structures indicative of palaeocurrent and surfaces interpreted as indicative of bar form and bar accretion direction. These surfaces of bar accretion are the boundaries of flood‐related bar increment elements, which are typically less abundant in outcrops than what would be desirable, particularly in large river deposits in which each flood mobilizes large volumes of sediment, causing flood‐increment boundary surfaces to be widely spaced. Cross‐strata set boundaries, on the other hand, are abundant and indirectly reflect the process of unit bar accretion, inclined due to the combined effect of the unit bar surface inclination and the individual bedform climbing angle, in turn controlled by changes in flow structure caused by local bar‐scale morphology. This work presents a new method to deduce the geometry of unit bar surfaces from measured pairs of cross‐strata and cross‐strata set boundaries. The method can be used in the absence of abundant flood‐increment bounding surfaces; the study of real cases shows that, for both downstream and laterally accreting bars, the reconstructed planes are very similar to measured bar increment surfaces.     

Integrating cellular automata,artificial neural network,and fuzzy set theory to simulate threatened orchards: application to Maragheh,Iran

Urbanization processes challenge the growth of orchards in many cities in Iran. In Maragheh, orchards are crucial ecological, economical, and tourist sources. To explore orchards threatened by urban expansion, this study first aims to develop a new model by coupling cellular automata (CA) and artificial neural network with fuzzy set theory (CA–ANN–Fuzzy). While fuzzy set theory captures the uncertainty associated with transition rules, the ANN considers spatial and temporal nonlinearities of the driving forces underlying the urban growth processes. Second, the CA–ANN–Fuzzy model is compared with two existing approaches, namely a basic CA and a CA coupled with an ANN (CA–ANN). Third, we quantify the amount of orchard loss during the last three decades as well as for the upcoming years up to 2025. Results show that CA–ANN–Fuzzy with 83% kappa coefficient performs significantly better than conventional CA (with 51% kappa coefficient) and CA–ANN (with 79% kappa coefficient) models in simulating orchard loss. The historical data shows a considerable loss of 26% during the last three decades, while the CA–ANN–Fuzzy simulation reveals a considerable future loss of 7% of Maragheh’s orchards in 2025 due to urbanization. These areas require special attention and must be protected by the local government and decision-makers.