Kalman滤波技术在地球化学数据处理中的应用

针对传统地球化学数据处理问题,引入Kallman滤波对地球化学数据进行降噪预处理,并对Kalman滤波技术应用于地球化学数据误差校正的可行性进行了系统研究,并以铜绿山1：5万水系中Cu的测量数据为例进行了验证分析,试验结果表明,Kalman滤波技术在对地球化学数据处理方面具有优势,适用于地球化学数据的误差校正。     

基于粗糙集理论的文本分类算法研究

文本分类是中文信息处理的重要研究领域。给文本分配一个或多个不同的类别,可提高文本检索和存储的处理效率。粗糙集是一种不需要任何先验信息的分类方法,通过对文本分词、过滤掉停用词之后把剩余的词语作为特征项,然后把文本用向量空间模型表示出来,将文本集转化成不带决策属性的信息系统,用粗糙集理论中核心内容属性约简实现对文本的分类。实验表明,该方法的查准率和查全率都有所提高。     

基于优势-直觉模糊粗糙模型的IT项目绩效审计评价规则获取

针对我国政府审计机关对政府投资的I`I}项目进行绩效审计评价规则知识获取的困难,考虑了条件属性取值 为优势精确值、分类结果为直觉模糊值的决策系统规则获取问题。首先比较条件属性值的大小,构建对象的优势部 域,再由对象邻域的直觉模糊值确定对象的上下近似;根据对象的上下近似和不同对象的直觉模糊值确定对象间的区 分关系,利用分辫矩阵给出知识约简和规则提取算法;最后将直觉模糊粗糙模型应用于政府I"I'项目绩效审计评价规 则的获取,得到了较为合理的IT项目绩效评价规则。     

半监督复杂结构数据降维方法

现有的一些典型半监督降维算法,往往在利用标记信息的同时却忽略了样本数据本身的流形特征,或者是对流形特征使用不当,导致算法性能表现不佳并且应用领域狭窄。针对上述问题提出了半监督复杂结构数据降维方法,同时保持样本数据的全局与局部的流形特征。通过设置适当的目标函数,使算法结果能有更广泛的应用场合,实验证明了算法的有效性。     

知识的约简研究

本文首先给出了知识约简问题的形式定义,然后详细描述了知识库中面向范畴的约简,面向属性的约简和面向规则的约简方法,分别提出了面向属性的约简算法和面向规则的约简算法,最后进行了一些讨论。     

一个基于加权和组合降维的web文本分类系统

设计了一个web文本分类系统,采用了基于统计分析和粗糙集组合的方法进行降维;降维时考虑了属性的位置信息,采用加权方式标注属性的不同重要性,以达到提高分类速度和分类准确度的目的。     

Attribute Selection Based on Rough Set Theory for Electromagnetic Interference (EMI) Fault Diagnosis

Electromagnetic emissions are radiated from every part of a personal computer motherboard, thus producing electromagnetic interference (EMI). EMI has an adverse effect on the surrounding environment because EMI could cause malfunctions or fatal problems in other digital devices. EMI engineers diagnose motherboard EMI problems using the electromagnetic noise data measured by the spectrum analyzer. Finding the sources (e.g., PS2, USB, VGA) of electromagnetic noise is a time-consuming process. The attribute selection and fault diagnosis was developed based on the advantage of rough set theory (RST). RST is a novel data mining approach for dealing with vagueness and uncertainty. It can be used to find hidden patterns in data sets. In this study, the basic rough set theory concepts are introduced. The rough set approach enables one to discover the minimal subsets of condition attributes associated with the motherboard EMI fault diagnosis problem. The operating sequence includes data collection, data preprocessing, discretization, attribute reduction, reduction filtering, rule generation, and classification accuracy. Historical EMI noise data, colleted from a famous motherboard company in Taiwan, were used to generate diagnostic rules. Our research result (average diagnostic accuracy of 80% above) shows that the RST model is a promising approach for EMI diagnostic support systems.     

基于局部线性投影的三维旋转人脸识别

本文在基于三维形态学模型的人脸识别研究中,运用局部线性投影算法(ProjectiveLLE,PLLE)取代了普遍使用的经典降维方法PCA,在高维空间中减小了降维过程中的线性失真。有效提高了所构建的三维形态学模型的质量,经实验证明该算法对于提高拟合的精度和大角度旋转人脸的识别率都取得了比较理想的效果。     

Analysis and Reduction of Ultrasonic Pitting Defects on Hard Disk Surfaces

It has become of paramount importance to be able to perform failure analysis of defects on hard disk surfaces quickly and accurately. In this study, ultrasonic pitting defects on hard disk surfaces were investigated. A new electrical tagging pattern system, which directly translated the channel bits to magnetic transitions during writing of the magnetic pattern around a defect, was used in the failure analysis of magnetic recording disks to mark defective sectors. With the help of the Kerr magneto-effect, the defective sectors were effectively located for further failure analysis. Results of the failure analysis revealed that there was 30% to 40% loss of the recorded magnetic bit signal due to an increase in the gap between a recording head and a hard disk surface with ultrasonic pitting defects. The experiments performed indicated that low ultrasonic power for disk cleaning could reduce the ultrasonic pitting defects significantly. The maximum failure rate due to single-type ultrasonic pitting defects was reduced from 33.4% to 16.7%, while the maximum failure rate due to cluster-type ultrasonic pitting defects was reduced from 11.1% to 5%.     

A bandwidth latency tradeoff for broadcast and reduction

The “fractional tree” algorithm for broadcasting and reduction is introduced. Its communication pattern interpolates between two well known patterns—sequential pipeline and pipelined binary tree. The speedup over the best of these simple methods can approach two for large systems and messages of intermediate size. For networks which are not very densely connected the new algorithm seems to be the best known method for the important case that each processor has only a single (possibly bidirectional) channel into the communication network.