基于粗糙集的K-均值聚类算法在图像分割中的应用

结合粗糙集理论和K-均值聚类算法,提出了一种图像的粗糙聚类分割方法,试验结果表明,其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。     

A MODEL FOR QUANTITATIVELY ESTIMATING SHORT-RANGE PRECIPITATION BASED ON GMS DIGITALIZED CLOUD MAPS—PART Ⅱ:ASSESSMENT OF RESULTS FROM THE MODEL FOR SATELLITE-IMAGE QUANTITATIVELY ESTIMATING PRECIPITATION

This is Part Ⅱ of this series.It introduces the technique for recognizing MαCS phased properties and its precipitation center or centers by means of dynamic digitalized cloud maps and presents the assessment of the effectiveness of the model proposed in Part Ⅰ as to its fitting and forecasting accuracy.     

Assessment of three numerical solution strategies for gravity field recovery from GOCE satellite gravity gradiometry implemented on a parallel platform

 The recovery of a full set of gravity field parameters from satellite gravity gradiometry (SGG) is a huge numerical and computational task. In practice, parallel computing has to be applied to estimate the more than 90 000 harmonic coefficients parameterizing the Earth's gravity field up to a maximum spherical harmonic degree of 300. Three independent solution strategies (preconditioned conjugate gradient method, semi-analytic approach, and distributed non-approximative adjustment), which are based on different concepts, are assessed and compared both theoretically and on the basis of a realistic-as-possible numerical simulation regarding the accuracy of the results, as well as the computational effort. Special concern is given to the correct treatment of the coloured noise characteristics of the gradiometer. The numerical simulations show that the three methods deliver nearly identical results—even in the case of large data gaps in the observation time series. The newly proposed distributed non-approximative adjustment approach, which is the only one of the three methods that solves the inverse problem in a strict sense, also turns out to be a feasible method for practical applications. Received: 17 December 2001 / Accepted: 17 July 2002 Acknowledgments. We would like to thank Prof. W.-D. Schuh, Institute of Theoretical Geodesy, University of Bonn, for providing us with the serial version of the PCGMA algorithm, which forms the basis for the parallel PCGMA package developed at our institute. This study was partially performed in the course of the GOCE project `From E?tv?s to mGal+', funded by the European Space Agency (ESA) under contract No. 14287/00/NL/DC. Correspondence to: R. Pail     

集群系统进程迁移机制研究

进程迁移是提高集群系统整体性的基础机制之一。作者在本文中首先详细地论述了进程迁移机制的关键技术，然后描述了在集群系统中PVM迁移原理，接着重点分析了在Linux集群中进程迁移算法的设计，最后对集群系统中与进程迁移机制相关的技术做了讨论。     

华北中强地震前Morishita播散指数空间演化特征及其应用

研究了华北中强地震前3年Morishita播散指数的空间演化，发现Iδ异常几乎都是首先在远离震中的地方出现，并逐步向未来震中集中，这种规律可为地震的地点预报提供重要信息。     

云南省金沙江流域低温霜冻灾害区划研究

选取5个指标,运用模糊聚类方法进行了云南金沙江流域低温霜冻灾害区划,将该流域划分为3个低温霜冻灾害区、9个低温霜冻灾害亚区,揭示了该流域低温霜冻灾害的地域差异性,为因地制宜地制定低温霜冻灾害防治规划及减灾防灾措施提供了科学依据。     

云南省金沙江流域作物病虫灾害区划研究

选取5个指标,运用模糊聚类方法进行了云南金沙江流域作物病虫灾害区划,将该流域划分为3个病虫灾害 区、8个病虫灾害亚区,揭示了该流域病虫灾害的地域差异性,为因地制宜地制定病虫灾害防治规划及减灾防灾措施 提供了科学依据。     

云南省金沙江流域水土流失灾害区划研究

水土流失是云南金沙江流域的头号环境问题和重要自然灾害。选取8个指标,运用模糊聚类方法进行了云 南金沙江流域水土流失灾害区划,将该流域划分为3个水土流失灾害区、9个水土流失灾害亚区,揭示了该流域水土 流失灾害状况的地域差异性,为因地制宜地制定水土流失灾害防治规划及措施提供了科学依据。     

分层聚类分析在水文地球化学分类中的应用

以福建省马坑矿区为例,对采集的水化学数据进行Q型聚类分析。分析结果表明,马坑矿区的地下水主要包括三种水化学类型:砂岩和花岗岩裂隙水类型、岩溶水类型及混合水类型,其中不同类型水的混合水与岩溶水距离较近,混合成因水(混合水)中又可细分为三种不同类型。通过分类大致了解区域不同含水层的水化学特征,为找出混合成因水,解决不同含水层的连通情况提供了可靠依据。     

中国物流集群的量化甄别与发育程度评价

基于交通运输、仓储与邮政业宏观统计数据,物流企业工商注册数据和物流POI数据,运用区位熵（LQ）、水平集聚区位熵（HCLQ）、物流就业密度（LED）和改进的物流企业占比系数（LEP）等指标,刻画了中国289个地级及以上城市的物流集群空间格局与演化过程,识别出不同类型物流集群的发育水平、类型和发展模式。结果表明：① 物流集群主要集中于胡焕庸线东侧,集群形态由组团式转变为区块式,呈现广覆盖和高集聚特征;数量演化经历了“快速下降”和“稳中有变”两个阶段,集中程度和运行效率稳步提升。② 21个成熟物流集群分布在16个省级行政单元中主要城市群的中心和次级中心城市,与政府物流规划衔接良好;43个新兴物流集群分布在21个省级行政单元,不同类型城市间分化显著。③ 物流集群在城市群尺度形成了由“主核—次核—一般节点”构成的多层级核心—边缘结构;在省级尺度形成了极核发展模式、网络化均衡发展模式,单核多点和多核多点的发展模式。