Study on strength reduction factors considering the effect of classification of design earthquake   总被引：1，自引：0，他引：1  

翟长海  谢礼立 《地震学报(英文版)》2006,19(3):299-310

Introduction The strength reduction factor is defined as the lateral yielding strength required to avoid yielding in the system when subjected to a given ground motion, to the lateral yielding strength required to maintain the displacement ductility ratio demand equal to a pre-determined target duc-tility ratio under the same ground motion. The strength reduction factors are not only the key fac-tors in determining seismic action for force-based seismic design, but also one of the key parame-t…  相似文献   

用雷达反射率作对流性降水和层状云降水自动分类   总被引：3，自引：3，他引：3  

吴涛吴翠红  万玉发舒防国 《气象科技》2006,34(5):610-614,I0005

为提高雷达定量测量降水的精度,利用武汉CINRAD/SA雷达反射率数据,研究提出了对流性降水和层状云降水自动分类算法(ACSS)。该算法在二维反射率结构场初步分类降水的基础上,识别亮带并从体扫描数据中提取降水的三维结构特征,然后对初步分类结果进行订正。试验表明,ACSS能较准确地实现对流性降水和层状云降水的自动分类,相对于只根据二维结构分类降水性能上有较大提高,主要表现在能正确识别出亮带特征明显的强层状云和对流核外沿的对流弱回波区。  相似文献   

Visualization of Volcanic Rock Geochemical Data and Classification with Artificial Neural Networks   总被引：1，自引：0，他引：1  

Juan Pablo Lacassie  Javier Ruiz del Solar  Barry Roser  Francisco Hervé 《Mathematical Geology》2006,38(6):697-710

An unsupervised neural network technique, Growing Cell Structures (GCS) was used to visualize geochemical differences between four different island arc volcanic rock types: basalts, andesites, dacites and rhyolites. The output of the method shows the cluster structure of the dataset clearly, and the relevant geochemical patterns and relationships between its variables. The data can be separated into four clusters, each associated with a specific volcanic rock type (basalt, andesite, dacite and rhyolite), according to a unique combination of major element concentrations. Following clustering, performance of the trained GCS network as a classifier of volcanic rock type was tested using two test datasets with major element concentration data for 312 and 496 island arc volcanic rock samples of known volcanic type. Preliminary classification results are promising. In the first test dataset 94% of basalts, 76% of andesites, 83% of dacites and 100% of the rhyolites were classified correctly. Successful classification rates in the second dataset were 100%, 80%, 77%, and 98% respectively. The success of the analysis suggests that neural networks analysis constitutes a useful analytical tool for identification of natural clusters and examination of the relationships between numeric variables in large datasets, and that can be used for automatic classification of new data.  相似文献   

Factors influencing determination of shale classification indices and their correlation to mechanical properties     

Hisham T. Eid 《Geotechnical and Geological Engineering》2006,24(6):1695-1713

The influence of sample preparation procedure on the measured classification indices such as clay-size fraction, liquid limit, and plastic limit of shales was investigated. Shale samples covering a wide range of composition and plasticity were tested using standard and modified preparation procedures to yield quantitative data required for this investigation. The study specifies the range of shale plasticity in which the measured values of clay-size fraction and liquid limit are sensitive to hydrometer specimen size and rehydration time, respectively. The study also revealed that the degree of shale particle disaggregation has an important influence on the measured clay-size fraction and liquid limit. This influence is maximized for shales with intermediate plasticity and can be interpreted in terms of particle size and shape. Correlations were established between classification indices derived from standard and modified sample preparation procedures. It is recommended to use these correlations to adjust shale classification indices derived from standard sample preparation procedures usually utilized by commercial laboratories. Such correlations help in creating a universally followed procedure for better estimation of shale engineering properties and reliable interpretation of case histories involving shale formations.  相似文献   

利用机载LIDAR双次回波高程之差分类激光脚点   总被引：6，自引：5，他引：6  

张小红 《测绘科学》2006,31(4):48-50

机载LIDAR技术已经引起了测绘界的浓厚兴趣,有可能给测绘领域带来一场新的技术革命。机载LI-DAR技术的硬件设备在国外已相对成熟,而机载LIDAR的数据后处理算法仍然处于研究发展阶段,还有诸多问题没有得到解决,其关键之一就是机载LIDAR数据的滤波与分类。本文首先对已有的滤波分类方法进行了综合评价,并指出了各自的局限。然后提出利用两次回波信号的高程数据来实现对机载LIDAR数据的分类。首次分类后得到植被激光脚点点集和地面及房屋激光脚点点集。而房屋上的激光脚点要高出地面上的激光脚点数米之多,简单利用阈值法就可以进一步分类出房屋激光脚点和地面激光脚点。也可以先经过滤波处理将地面激光脚点去掉,然后利用两次回波信号的高程数据来分类自然植被激光脚点和人工地物激光脚点。实验证明所提方法简单有效,算法简单实用,特别适用于分类植被激光脚点。  相似文献   

基于RBF神经网络的遥感影像分类器设计   总被引：2，自引：0，他引：2  

刘书华  舒宁 《测绘信息与工程》2006,31(2):10-12

设计了一种运用径向基函数神经网络进行遥感影像分类的监督分类器,以实际的遥感光谱影像分类为例,将分类效果同传统的最小欧氏距离法分类进行比较,探讨了RBF分类的优越性,结果表明RBF神经网络是一种更为有效的图像分类器。  相似文献   

网络上分级统计地图制图软件的设计与开发   总被引：1，自引：0，他引：1  

章莉萍  郭庆胜 《测绘信息与工程》2006,31(3):47-49

分析了网络环境中分级统计图表达信息的特点,阐述了交互式分级统计图的设计方法和思路,运用JavaApplet设计并实现了网络上分级统计地图制图子系统。  相似文献   

基于面向对象和规则的遥感影像分类研究   总被引：54，自引：4，他引：54  

陈云浩  冯通  史培军  王今飞 《武汉大学学报(信息科学版)》2006,31(4):316-320

讨论了面向对象和规则的光学遥感影像分类方法。首先利用多尺度分割形成影像对象，建立对象的层次结构，计算对象的光谱特征、几何特征、拓扑特征等，利用对象、特征形成分类规则，并通过不同对象层间信息的传递和合并实现对影像的分类。并以北京城市土地利用分类为例，对该方法进行了验证。  相似文献   

基于形式化本体的基础地理信息分类   总被引：3，自引：0，他引：3  

李霖  王红 《武汉大学学报(信息科学版)》2006,31(6):523-526

从本体概念出发,以认知分类和现有的本体分类方法为基础,将地理信息概念分为元概念和复合概念两大类,并基于一定的约束条件,根据地理信息概念的元属性,以形式化方法实现基础地理信息的分类.  相似文献   

基于地物空间信息的浮动先验概率最大似然分类研究   总被引：4，自引：3，他引：4  

刘良云  王纪华  赵春江  宋晓宇  李存军  张超 《遥感学报》2006,10(2):227-235

利用遥感影像对地物进行分类识别时，既需要考虑地物波谱信息，也需要考虑其空间信息。现有遥感分类方法主要集中在利用像素的波谱信息，对各个像素进行独立分类，忽略了地物空间信息。考虑到传统最大似然分类（MLC）方法包括先验概率和条件概率密度函数两个核心环节，提出基于空间信息的浮动先验概率MLC方法，融合空间信息和波谱信息，以提高分类精度。在分析地物空间信息的基础上，总结了基于空间信息的浮动先验概率确定原则和依据，包括地物几何空间特征、情景特征、临近像素空间自相关定律、景观参数等，并设计了基于地物空间特征和临近像素空间自相关定律的浮动先验概率确定算法和分类流程。通过分类试验和误差矩阵分析，结果表明：基于空间特征和临近像素空间自相关定律的浮动先验概率MLC方法，能够融合地物的波谱信息和空间信息，克服最小距离、MLC等基于像素波谱信息的分类方法的缺点，显著提高地物分类精度。  相似文献