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。     

灰色聚类法在常州市第Ⅱ承压地下水水质评价中的应用

在灰色聚类方法原理的基础上，探讨了如何通过白化函数生成灰色聚类矩阵，并以常州市第Ⅱ承压地下水为例进行了水质评价，评价结果表明，常州市大部分第Ⅱ承压地下水水质优良，达到了Ⅰ类水，未遭受外来物质的污染，评价结果符合实际情况。     

数据挖掘技术在水文预报中的应用及水文预报发展趋势研究

数据挖掘作为知识发现过程中的重要步骤,是从大型数据库中提取未知的、有价值的和可操作性的关系、模式和趋势用于决策支持的过程。我国目前在防洪领域存在着大量水文数据,如何充分有效地利用各种智能算法对这些数据进行分析与挖掘,以形成相应的水文预报模型进行准确的水文预报是防洪决策支持系统完善和发展的重要方面。本文首先全面地介绍数据挖掘的功能分类及以数据挖掘为基础的水文预报体系,然后对数据挖掘技术在水文预报中的应用进行了探讨和研究。     

Road Surface Modeling and Representation from Point Cloud Based on Fuzzy Clustering

A scheme for an automatic road surface modeling from a noisy point cloud is presented. The normal vectors of the point cloud are estimated by distance-weighted fitting of local plane. Then, an automati...     

空间数据模糊聚类的有效性评价

基于模糊划分中存在的分类不确定性因素和空间数据的空间位置特征,提出了一种新的空间数据模糊聚类有效性函数。实验结果表明,这种新的有效性函数能够对模糊聚类结果的有效性进行正确的评价,特别是对于空间数据模糊聚类有效性评价,其分类效果较理想,同其他有效性指标相比,能得到较优的分类数。     

Clustering stochastic point process model for flood risk analysis

Since the introduction into flood risk analysis, the partial duration series method has gained increasing acceptance as an appealing alternative to the annual maximum series method. However, when the base flow is low, there is clustering in the flood peak or flow volume point process. In this case, the general stochastic point process model is not suitable to risk analysis. Therefore, two types of models for flood risk analysis are derived on the basis of clustering stochastic point process theory in this paper. The most remarkable characteristic of these models is that the flood risk is considered directly within the time domain. The acceptability of different models are also discussed with the combination of the flood peak counted process in twenty years at Yichang station on the Yangtze river. The result shows that the two kinds of models are suitable ones for flood risk analysis, which are more flexible compared with the traditional flood risk models derived on the basis of annual maximum series method or the general stochastic point process theory. Received: September 29, 1997