边坡稳定性分类评价的同伦模糊C-均值聚类算法     

文建华  周翠英  黄林冲  程晔 《岩土力学》2012,33(5):1457-1461

针对单一模糊C-均值聚类算法对初始聚类中心初值敏感性问题,引入同伦理论,提出了同伦模糊C-均值聚类算法。以三峡库岸研究程度较高的36个边坡为对象,采用同伦模糊C-均值聚类算法对边坡的稳定性进行分类,研究边坡最佳分类级数和算法的收敛性、可靠性。边坡聚类结果研究表明,同伦模糊C-均值聚类算法对初始聚类中心的选取没有明显的依赖性,是一个具有全局最优解的聚类方法,其结果明显好于单一模糊C-均值聚类算法。  相似文献   

南北地震带北部5次（1561~1920年）M≥7级地震触发关系研究   总被引：7，自引：1，他引：6       下载免费PDF全文

韩竹军  董绍鹏  谢富仁  安艳芬 《地球物理学报》2008,51(6):1776-1784

以南北地震带北部的青藏高原东北边缘与华北构造区过渡部位为例,通过建立地震构造模型,计算静态库仑破裂应力改变量（ΔCFS）,研究了该区1561~1920年360年间5次M≥7级地震之间的触发过程.结果表明,在1561年罗山东麓7¹/₄级地震之后,下一次地震无一例外地发生在前面地震产生的应力触发区（ΔCFS>0）.在4条被触发的发震断裂中,有3条发震断裂的平均ΔCFS>0.2×10⁵ Pa,最大可达0.62×10⁵ Pa,超出目前普遍认为触发应力阀值（0.1×10⁵ Pa）.根据断裂库仑破裂应力变化量（ΔCFS）和构造应力累计率（δτ）,计算获得了下一次地震发生的提前量（ΔT）,地震活动提前量最大可以达到160a.在一条重要活动构造带或地区上,一次地震发生对下一次地震的触发缩短了地震重复发生所需要的累积时间,使得地震可以提前发生,这一方面使得某一特定的发震断裂在时间尺度表现出准周期性,另一方面使得空间上不同发震断裂的地震活动表现出丛集发生的现象.此项研究有助于认识断裂间相互作用特点、揭示地震丛集发生规律以及预测未来地震危险区.  相似文献   

基于权重赋值法与灰色聚类法评价虾蛏串联养殖池塘的生态修复效果     

鲍格格  赵淳朴  梅泊承  张顺  徐善良  徐继林 《海洋与湖沼》2022,53(1):206-214

水产养殖业的尾水排放已成为水域生态环境的污染源之一,为探究凡纳滨对虾-缢蛏串联养殖模式的生态修复效果,对凡纳滨对虾-缢蛏串联养殖池塘的水生态进行周年跟踪测定,并采用权重赋值法与灰色聚类法对其生态修复效果进行评价.结果 显示:串联模式下浮游植物的丰度介于6.8× 105～2.5×108 cell/L,生物量为2.04～6...  相似文献   

丽江市黑龙潭地区水文地质条件分析     

雷风平  王锦国  赵燕容  陈长生  黄华  周云 《中国煤炭地质》2019,(4):51-56,67

以丽江市玉龙县境内的黑龙潭地区为主要研究对象,总结了已有的水文地质资料,分析了九子海-黑龙潭地区的岩性、构造等特征。通过对研究区内及周边泉的调查研究,认为北衙组中段、上段的灰岩、白云质灰岩是研究区的主要含水层,地形切割上述含水层使得地下水出露成泉。对水样进行了水化学聚类分析和氢氧同位素分析,发现含水层主要接受大气降水的渗透补给。按照水力联系对泉点进行了划分。根据研究区内及周边地区的泉点分布分析了地下空间的特点和地下水的联系。研究结果对泉群的利用、保护具有参考价值。  相似文献   

GML数据的整体同构压缩算法研究     

张海涛  闾国年  张书亮  原立峰  姜杰 《地理与地理信息科学》2009,25(2)

在分析传统的GML,数据压缩技术特点的基础上,提出GMI数据整体同构压缩方法:以GMI,文档中的Fea-ture元素为基元,利用标签索引编码实现语义的同构压缩;以GMI空间数据的聚类分区结果建立分组局部坐标参考系,利用坐标参考系转换实现空间内容的同构压缩.实验证明:该压缩算法的存储空间消耗、查询处理速度等性能均优于传统方法,对研究GMI数据的存储、查询与传输等技术具有一定的参考价值.  相似文献   

泛型聚类排序3DR树批量构建算法   总被引：1，自引：0，他引：1  

何珍文 《地理与地理信息科学》2009,25(3)

提出一种新的泛型3DR树批量构建算法,其核心思想是通过三维空间聚类和空间排序操作,使得在空间位置上邻近的空间对象在R树中处于尽量邻近的叶节点上,从而减少这些空间对象之间的交叠范围.对于给定的三维空间对象集合,首先依照其中心点进行距离相关性聚类,分为K类;对每类空间对象集进行3个分量方向上的扫描排序,再对每类的中心位置进行扫描排序;最后采用倒序批量构树方法构建R树.该算法比已有的R树构建算法有更高的时间和空间效率.  相似文献   

Fingerprinting upland sediment sources: particle size‐specific magnetic linkages between soils,lake sediments and suspended sediments     

Robert G. Hatfield  Barbara A. Maher 《地球表面变化过程与地形》2009,34(10):1359-1373

Accelerated erosion of fine‐grained sediment is an environmental problem of international dimensions. Erosion control strategies and targeting of mitigation measures require robust and quantitative identification of sediment sources. Here, we use magnetic ‘fingerprinting’ to characterize soils, and examine their affinity with and contribution to suspended sediments transported within two subcatchments feeding Bassenthwaite Lake, northwest England. A high‐resolution soil magnetic susceptibility survey was made using a field susceptometer (ZH Instruments, SM400 probe). Combining the spatial and vertical (down‐profile) soil magnetic data, a subset of soil profiles was selected for detailed, laboratory‐based magnetic remanence analyses. The magnetic properties of the catchment soils are highly particle size‐dependent. Magnetic analyses were performed on the 31–63 µm fraction, for particle size‐specific comparison both with the suspended sediments and lake sediments. Fuzzy cluster analysis groups the soil magnetic data into six clusters, apparently reflecting variations in parent material and horizon type, with three magnetically hard soils as unclassified outliers. Examination of the cluster affinity of the soils, suspended sediments and lake sediments indicates that topsoils of the upper Newlands Valley and subsoils around Keskadale Beck are a major source of the Newlands Beck suspended load, and the recent (post‐nineteenth century) sediments in the deep lake basin. Older lake sediments show strong affinity with a small number of the Derwent suspended sediments and one of the Glenderamackin soils. A large number of Derwent suspended sediments show no affinity with any of the soils or lake sediments, instead forming a coherent, discrete and statistically unclassified group, possibly resulting from mixing between the magnetically hard subsoils of the medium to high‐altitude Glenderamackin and Troutbeck areas and softer, lower altitude Glenderamackin soils. The lack of any affinity of these suspended sediments with the lake sediments may indicate deposition along the Derwent flood plain and/or in the shallow delta of Lake Bassenthwaite. Particle size‐specific magnetic fingerprinting is thus shown to be both highly discriminatory and quantitatively robust even within the homogeneous geological units of this catchment area. Such a methodological approach has important implications for small–large scale catchment management where sources of sediment arising from areas with uniform geology have been difficult to determine using other approaches, such as geochemical or radionuclide analyses. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

宽频带模态识别算法中极点的自动选取     

孙鑫晖  张令弥 《地震工程与工程振动》2009,29(1)

摘在试验模态分析中,确定系统阶次以及极点的正确选择是一个非常重要的问题。到目前为止,这项工作一般是由人工来完成。但是在复杂或者大阻尼结构中,这个过程尤其繁琐并且耗时。本文中采用模糊聚类方法对极点进行分类,实现了极点的自动选取,减少了人工选取的工作量。  相似文献   

Estimation of river flow by artificial neural networks and identification of input vectors susceptible to producing unreliable flow estimates   总被引：1，自引：0，他引：1  

Elcin Kentel   《Journal of Hydrology》2009,375(3-4):481-488

Reliable river flow estimates are crucial for appropriate water resources planning and management. River flow forecasting can be conducted by conceptual or physical models, or data-driven black box models. Development of physically-based models requires an understanding of all the physical processes which impact a natural process and the interactions among them. Since identification of the relationships among these physical processes is very difficult, data-driven approaches have recently been utilized in hydrological modeling. Artificial neural networks are one of the widely used data-driven approaches for modeling hydrological processes. In this study, estimation of future monthly river flows for Guvenc River, Ankara is conducted using various artificial neural network models. Success of artificial neural network models relies on the availability of adequate data sets. A direct mapping from inputs to outputs without consideration of the complex relationships among the dependent and independent variables of the hydrological process is identified. In this study, past precipitation, river flow data, and the associated month are used to predict future river flows for Guvenc River. Impacts of various input patterns, number of training cycles, and initial values assigned to the weights of the connections are investigated. One of the major weaknesses of artificial neural networks is that they may fail to generate good estimates for extreme events, i.e. events that do not occur at all or often enough in the training data set. It is very important to be able to identify such unlikely events. A fuzzy c-means algorithm is used in this study to cluster the training and validation input vectors into regular and extreme events so that the user will have an idea about the risk of the artificial neural network model to generate unreliable results.  相似文献   

模糊聚类在不良地质洞段红外探水中的应用     

张雪峰  叶祖圣 《地震学刊》2010,(6):698-701

在玉昆铁路柿花树隧道不良地质发育的洞段进行红外探水工作期间,常用的分析方法有时无法预判掌子面前方是否存在隐伏水体或含水构造。为了提高红外探水短距离预报的准确率,用模糊聚类法将掌子面测点场强的数据分类,根据开挖传递的地质信息,研究模糊聚类结果的变化规律、突水风险与岩体破碎程度之间的关系。实践证明,模糊聚类法和常用分析方法的结合,使红外探水取得了较好的预判效果。  相似文献