Generalized Possibilistic Fuzzy C-Means with novel cluster validity indices for clustering noisy data

A generalized form of Possibilistic Fuzzy C-Means (PFCM) algorithm (GPFCM) is presented for clustering noisy data. A function of distance is used instead of the distance itself to damp noise contributions. It is shown that when the data are highly noisy, GPFCM finds accurate cluster centers but FCM (Fuzzy C-Means), PCM (Possibilistic C-Means), and PFCM algorithms fail. FCM, PCM, and PFCM yield inaccurate cluster centers when clusters are not of the same size or covariance norm is used, whereas GPFCM performs well for both of the cases even when the data are noisy. It is shown that generalized forms of FCM and PCM (GFCM and GPCM) are also more accurate than FCM and PCM. A measure is defined to evaluate performance of the clustering algorithms. It shows that average error of GPFCM and its simplified forms are about 80% smaller than those of FCM, PCM, and PFCM. However, GPFCM demands higher computational costs due to nonlinear updating equations. Three cluster validity indices are introduced to determine number of clusters in clean and noisy datasets. One of them considers compactness of the clusters; the other considers separation of the clusters, and the third one considers both separation and compactness. Performance of these indices is confirmed to be satisfactory using various examples of noisy datasets.     

Simulation-based multi-objective system optimization of train traction systems

A holistic framework for multi-objective optimization of the traction system configuration of trains with mixed-integer decision variables is presented. Rail vehicles have to be energy-efficient and must be operated on a tight schedule. Furthermore, the number of decision variables to fulfill these objectives is large, and some components (like motors and gears) can only be chosen from a small set of discrete elements. In this work, the overall optimization is achieved by a two level approach: The Pareto front of optimal system configurations is obtained by a multi-objective mixed-integer elitist genetic algorithm (GA) on the upper-level. To capture the influence of a specific system configuration on travel time and energy consumption, a suitable train trajectory optimizer is developed and employed in the lower-level. The train trajectory optimization is solved by sequential quadratic programming (SQP) and considers the power losses of the different components. A case study is presented which highlights the benefits of the holistic multi-objective optimization.     

基于色彩特征的无参考彩色图像质量评价

彩色图像质量评价(Color Image Quality Assessment,C-IQA)作为一种图像质量评价系统,与其他图像质量评价系统对彩色图像只是简单地将原图像转换为灰度图像进行评价不同,不仅考虑图像在灰度尺度下的质量评价,而且需要对图像的色彩表现做出评价。提出一种基于色彩特征的彩色图像质量的数学评价模型,在考虑亮度特征的同时,加入了色调、色饱和度和色彩熵等色度特征来进行C-IQA。在LIVE图像数据库中进行实验,可以发现模型预测结果与图像实际质量保持高度一致。     

多传感器通道多点数据并行高速采集器设计

为解决传统方法设计的采集器传感器通道单一、运行功耗大、抗干扰能力差及采集效率低问题,设计了一种多传感器通道多点数据并行高速采集器;分析数据采集器工作原理,先对影响采集器高效运行的高频率噪音和高频载波两大干扰因素进行过滤处理;同步采集数据信号,对数据进行校验,通过数据采集处理,实现多传感器通道多点数据并行高速采集器的设计;实验结果表明,改进的数据采集器运行功耗小,抗干扰能力强,采集效率高。     

基于Hadoop的K-means聚类算法的实现

文中针对传统并行K-means聚类算法时间复杂度比较高的问题,结合Hadoop平台以及MapReduce编程模型的优势,提出了利用Hadoop及MapReduce编程模型实现大数据量下的K-means聚类算法。其中,Map函数完成每条记录到各个质心距离的计算并标记其所属类别,Reduce函数完成质心的更新,同时计算每条数据到其所属中心点的距离,并累计求和。通过实验,验证了K-means算法部署在Hadoop集群上并行化运行,在处理大数据时,同传统的串行算法相比,确实能够降低时间复杂度,而且表现出很好的稳定性和扩展性。     

基于FPGA的轨道振动信号数字监测接收机设计

设计了一种基于FPGA的轨道振动信号数字监测接收机,详细阐述了接收机的数据流走向及其振动信号频域分析的实现.设计中以Altera的cycloneⅢ系列芯片EP3c25Q240C8为硬件平台,以QuartusⅡ9.1为软件平台,数据存储缓存单元使用ISIS公司的IS61NLP102418,频域分析则使用1024个点的FFT,进行功率谱估计.     

Positive approximation and converse approximation in interval-valued fuzzy rough sets

Methods of fuzzy rule extraction based on rough set theory are rarely reported in incomplete interval-valued fuzzy information systems. Thus, this paper deals with such systems. Instead of obtaining rules by attribute reduction, which may have a negative effect on inducting good rules, the objective of this paper is to extract rules without computing attribute reducts. The data completeness of missing attribute values is first presented. Positive and converse approximations in interval-valued fuzzy rough sets are then defined, and their important properties are discussed. Two algorithms based on positive and converse approximations, namely, mine rules based on the positive approximation (MRBPA) and mine rules based on the converse approximation (MRBCA), are proposed for rule extraction. The two algorithms are evaluated by several data sets from the UC Irvine Machine Learning Repository. The experimental results show that MRBPA and MRBCA achieve better classification performances than the method based on attribute reduction.     

软件体系结构动态演化的条件超图文法及分析

针对目前.软件体系结构动态演化描述方法的不足,提出用约束超图表示软件体系结构,用左右应用条件刻画软件体系结构动态演化的前断言和后断言,用条件超图文法建模软件体系结构动态演化过程.通过案例分析,讨论了如何构建条件超图文法并应用于软件体系结构动态演化.在此基础上,建立软件体系结构动态演化的一致性条件定义,给出动态演化的一致性判定方法.最后,设计实验进行分析,验证了方法的有效性.     

基于树比较的Web页面主题信息抽取

为了从具有海量信息的Internet上自动抽取Web页面的信息,提出了一种基于树比较的Web页面主题信息抽取方法。通过目标页面与其相似页面所构建的树之间的比较,简化了目标页面,并在此基础上生成抽取规则,完成了页面主题信息的抽取。对国内主要的一些网站页面进行的抽取检测表明,该方法可以准确、有效地抽取Web页面的主题信息。     

基于Socks5代理的移动SSL VPN系统研究与实现

针对传统基于IPSec和SSL技术的移动VPN的不足,提出一种基于Socks5代理的移动SSL VPN解决方案.分析了系统的实现原理和过程,并介绍了系统的总体框架和工作流程.最后对系统进行了实现和测试,并对系统安全性能和接入、传输效率进行了分析.