基于变网格聚类的离群数据的研究

随着计算机技术的迅速发展,计算机在过程控制中起着越来越重要的作用,在集散控制系统中,上位机通过PCU(Process ControlUnit)传送来的数据进行分析处理而后对PCU实现参数整定、报警与管理。因此这一领域的数据挖掘方法研究具有十分重要的意义。文章将根据这一领域的特殊情况,提出一种基于变网格的聚类分析算法分析过程数据库中的离群数据,从而实现系统的预测报警功能。     

安徽省旅游星级饭店地域差异研究

根据2000～2005年安徽省星级饭店统计资料,利用变异系数这一度量标准分析了安徽省饭店在时间序列上和星级结构上的地域差异,结果表明:随着时间的变化饭店总数在各市间的差异在渐渐缩小.星级结构上五星级饭店地域分异程度最大,其次依次为一星级、四星级、三星级和二星级,通过安徽省各市国内旅游收入区位商和餐饮住宿业就业人员区位商与各市星级饭店数量相对水平的比较,找出不符合一般趋势的城市加以讨论.最后,运用SPSS分析软件对安徽省17个地市的星级饭店发展水平进行聚类分析,并讨论了运行结果所分出的4类城市,提出了饭店业发展的若干建议.     

影响我国主要粮食作物产量的气象因子研究

通过收集前人主要粮食作物气象产量预报的研究成果，将所得到的资料按作物进行分类，并进行归一化处理，使用系统聚类分析方法，以预报方程中的影响因子为指标，分区找出各区主要粮食作物产量的主、次要影响因子和影响时期，为大范围作物产量预报提供了科学依据。     

Self-organised clustering for road extraction in classified imagery

The extraction of road networks from digital imagery is a fundamental image analysis operation. Common problems encountered in automated road extraction include high sensitivity to typical scene clutter in high-resolution imagery, and inefficiency to meaningfully exploit multispectral imagery (MSI). With a ground sample distance (GSD) of less than 2 m per pixel, roads can be broadly described as elongated regions. We propose an approach of elongated region-based analysis for 2D road extraction from high-resolution imagery, which is suitable for MSI, and is insensitive to conventional edge definition. A self-organising road map (SORM) algorithm is presented, inspired from a specialised variation of Kohonen's self-organising map (SOM) neural network algorithm. A spectrally classified high-resolution image is assumed to be the input for our analysis. Our approach proceeds by performing spatial cluster analysis as a mid-level processing technique. This allows us to improve tolerance to road clutter in high-resolution images, and to minimise the effect on road extraction of common classification errors. This approach is designed in consideration of the emerging trend towards high-resolution multispectral sensors. Preliminary results demonstrate robust road extraction ability due to the non-local approach, when presented with noisy input.     

Space-time interaction amongst clusters of mining induced seismicity

Elementary cluster analysis of induced seismicity in a South African gold mine has shown that there is a clear interaction amongst the clusters; and that the level of the interaction is a function of the distance. The clusering algorithm used is an adaptation of the single-link cluster analysis which considers both three-dimensional space and time. A high level of interaction between the clusters is demonstrated from the cross-correlation analysis of seismic activity rates and radiated energy. A distinct decrease in the value of correlation coefficients was detectable as distance increased. This was somewhat surprising, considering the simplicity of the technique used. Since no attempt is made to study the physical mechanisms of interaction, these results are very preliminary, but interesting from an observational point of view.     

Multifractal modeling and spatial point processes

The multifractal model can be applied to spatial point processes. It provides new, approximately power-law type, expressions for their second-order intensity and K (r) functions. The box-counting and cluster dimensions are different but mutually interrelated according to multifractal theory. This approach is used to describe the underlying spatial structure of gold mineral occurrences in the Iskut River area, northwestern British Columbia. The box-counting and cluster dimensions for the example are estimated to be 1.335±0.077 and 1.219±0.037, respectively. The relatively strong clustering of the gold deposits is reflected by the fact that both values are considerably less than the corresponding Euclidean dimension (=2).     

金相分析中消除划痕的两种方法

介绍了两种在金相分析中采用模式识别技术,以距离聚类和角度类消除划痕的方法,使主体更加突出,分类评级更加准确,也降低了对试样的磨制要求。     

环境同位素和模糊聚类法研究堤坝渗漏

利用环境同位素方法对高水河堤防几个典型段进行了渗漏分析,查明了其地下水的渗漏来源,结果表明,江都船厂段T1#孔、小菜谭段T23#孔中的地下水为河水补给来源,T5#孔附近的黑鱼塘水为当地降雨补给,万寿宫段T7#孔中的地下水为河水和当地降雨的混合。由于环境同位素的分析方法只能定性的说明问题,笔者尝试应用模糊聚类方法,选取环境同位素和水化学值作为指标特征值,并赋与不同的权重,进行模糊聚类分析,分析结果与环境同位素、水化学分析结论一致。     

基于聚类有效性函数的面状地理实体聚类

为解决聚类数未知条件下面状地理实体的聚类问题,文中提出了一种基于聚类有效性函数的聚类方法。给出了适合面状地理实体k-中心点聚类算法的聚类有效性函数;将该有效性函数改写为适应度函数,设计了基于遗传算法的面状地理实体聚类算法。该算法在计算聚类数的同时能得到划分聚类结果。实验结果从一定程度上反映了数据集的结构信息特征。