Cross-scale analysis of cluster correspondence using different operational neighborhoods

Cluster correspondence analysis examines the spatial autocorrelation of multi-location events at the local scale. This paper argues that patterns of cluster correspondence are highly sensitive to the definition of operational neighborhoods that form the spatial units of analysis. A subset of multi-location events is examined for cluster correspondence if they are associated with the same operational neighborhood. This paper discusses the construction of operational neighborhoods for cluster correspondence analysis based on the spatial properties of the underlying zoning system and the scales at which the zones are aggregated into neighborhoods. Impacts of this construction on the degree of cluster correspondence are also analyzed. Empirical analyses of cluster correspondence between paired vehicle theft and recovery locations are conducted on different zoning methods and across a series of geographic scales and the dynamics of cluster correspondence patterns are discussed.      

多源遥感影像误匹配点剔除的粗糙模糊C-均值方法

简要概述了遥感影像匹配中,误匹配点剔除的常用方法.对SIFT特征描述子生成及其匹配、粗糙模糊C-均值方法聚类分析的原理方法进行了详细论述.针对SIFT方法匹配出的大量点对,将不同时相,不同传感器、不同分辨率影像广义划分为同分辨率和不同分辨率.基于同分辨率影像匹配点对问连线具有相同的距离及斜率、不同分辨率影像匹配点对间连线的延长线交于一点的几何约束条件,利用粗糙模糊C-均值模型聚类分析方法对点对快速剔除误匹配点后,对剔除的结果利用最小二乘方法进行精匹配,结果达到亚像素.最后,通过对不同时相、不同分辨率、不同传感器的多源遥感影像实验分析验证了该方法的适用性、可靠性及精确性.     

基于GIS的TM数据分类及辅助制图研究

本文初步研究了遥感、GIS和制图一体化实用技术方法。对黄土丘陵区和沙漠地区TM数据进行了特征信息分析;给出了分层分类和GIS辅助分类结果;经模糊推理和人机交互修改,将提“纯”的遥感专题数据作为GIS的动态信息源,对GIS进行扩充与更新;最后在GIS支持下分层提取专题图并进行辅助制图。     

FS方法及其在综合多项震兆中的应用

本文提出了一种模式识别方法--FS方法.该方法的特征取为某些论域上的模糊子集.先以每三个原始特征组成子分类器的特征集,“训练”这些分类器,然后对子分类器进行筛选,最后用筛选出的子分类器的“软”分类结果的加权平均作为判别函数,形成总的分类决策.将FS方法应用于综合多项震兆,并进行了一系列控制试验,还与地震学中几种常用的方法进行了对比试验.结果表明,FS方法是稳定和有效的.     

Fuzzy expert system for economic zonation of an ornamental slate deposit

Investigation of deposits for traditional extraction activities (metals and coal) has generally been based on determining grade, or content, of the required material. In order to apply the grade concept to an ornamental rock such as slate, it is first necessary to define the variables that determine both the geotechnical recovery rate for the rock mass — which conditions the size of the extracted blocks – and the aesthetic features of the slate — which define the quality of the slabs as potential roofing material.

For this research, geotechnical and aesthetic data for a slate deposit were collected from 16 continuous core borehole samples. A fuzzy expert system was then developed using this data, defining the rock mass recovery rate and slab quality in accordance with the criteria of a slate expert, producing as a final output a zonation of the deposit in terms of top quality slate, medium quality slate or waste.

A mathematical model based on fuzzy logic was chosen due to the fact that the boundaries between different quality groups in a deposit are not clearly distinguished. Moreover, quality also depends on a company's infrastructures for transformation of the blocks, and also on its commercial strategies.     

Statistical analysis for the hydrogeological evaluation of the fracture networks in hard rocks

The hydrogeological effectiveness of fracture sets is determined and evaluated by the fuzzy c-mean and hierarchical clustering. These cluster analyses combine the geological spatial attributes and the hydraulic relevant attributes of fractures. Based on the results of the clustering the fracture set volumes are estimated.     

Hydrogeochemical evolution of groundwater in a Mediterranean coastal aquifer, Mersin-Erdemli basin (Turkey)

In this study, hydrogeologic and hydrochemical information from the Mersin-Erdemli groundwater system were integrated and used to determine the main factors and mechanisms controlling the chemistry of groundwaters in the area and anthropogenic factors presently affecting them. The PHREEQC geochemical modeling demonstrated that relatively few phases are required to derive water chemistry in the area. In a broad sense, the reactions responsible for the hydrochemical evolution in the area fall into four categories: (1) silicate weathering reactions; (2) dissolution of salts; (3) precipitation of calcite, amorphous silica and kaolinite; (4) ion exchange. As determined by multivariate statistical analysis, anthropogenic factors show seasonality in the area where most contaminated waters related to fertilizer and fungicide applications that occur during early summer season.     

基于粗糙集的K--均值聚类算法在遥感影像分割中的应用

结合粗糙集理论和K——均值聚类算法，提出一种遥感影像的粗糙聚类分割方法。根据遥感影像中特征属性的相互依赖关系，应用粗糙集理论的等价关系。求出K——均值聚类所需要的初始类的个数和均值。然后采用聚类算法对图像进行分割。实验结果表明该方法比随机选取聚类的中心点和个数减少了运算量．提高了分类精度和准确性。     

内蒙古色尔腾山山前断裂(乌句蒙口-东风村段)的断层活动与古地震事件

通过对色尔腾山山前断裂乌句蒙口 -东风村段的遥感资料解释、野外地质地貌考察 ,并通过对重点地段的古地震探槽开挖 ,获得了该断裂段晚更新世晚期以来的垂直位移速率是 0 88～ 1 83mm a ,全新世中期以来的垂直位移速率是 0 89mm a。通过 2个大型探槽的开挖、古地震事件分析和相关堆积物的断代研究 ,以及用逐次限定方法分析整个断层段上的古地震事件 ,认定该断裂段上全新世以来发生了 5次古地震事件 :事件 1发生在距今 90 0 0± 130 0年 ,事件2发生在距今 6 5 0 0± 5 0 0年 ,事件 3发生在距今 5 5 70年左右 ,事件 4发生在距今 4 2 0 0± 30 0年 ,事件 5发生在距今 32 5 0± 2 5 0年。晚更新世晚期到距今 1万年之间 ,古地震事件很不完整。全新世以来的 5次古地震事件表现出一定的丛集特征。最早的一丛事件发生在距今 890 0年左右 ,第2丛发生在距今 6 5 0 0～ 5 70 0年之间 ,第 3丛事件发生在距今 32 5 0～ 4 2 0 0年之间。第 1丛与第 2丛古地震事件之间间隔为 2 4 0 0年左右 ,而第 2丛与第 3丛古地震事件之间仅间隔 15 70年左右。距今 32 5 0年以来 ,该断裂段上还没有发生过错断地表的地震事件 ,已经超出了古地震丛之间的重复间隔。因此 ,它是色尔腾山前活动断裂带上具备潜在危险的一个活动断裂段。     

Fuzzy neural network models for liquefaction prediction

Integrated fuzzy neural network models are developed for the assessment of liquefaction potential of a site. The models are trained with large databases of liquefaction case histories. A two-stage training algorithm is used to develop a fuzzy neural network model. In the preliminary training stage, the training case histories are used to determine initial network parameters. In the final training stage, the training case histories are processed one by one to develop membership functions for the network parameters. During the testing phase, input variables are described in linguistic terms such as ‘high’ and ‘low’. The prediction is made in terms of a liquefaction index representing the degree of liquefaction described in fuzzy terms such as ‘highly likely’, ‘likely’, or ‘unlikely’. The results from the model are compared with actual field observations and misclassified cases are identified. The models are found to have good predictive ability and are expected to be very useful for a preliminary evaluation of liquefaction potential of a site for which the input parameters are not well defined.