一种融合无监督聚类的层次向量机多类分类方法

层次支持向量机（SVM）是多类分类方法应用中的研究热点。针对SVM的分类面仅由支持向量决定的理论,提出一种基于无监督聚类方法来预抽取支持向量,训练向量机;并分析现有多类分类方法所存在的弊端,基于综合考虑节点的类集合可分性,设计一种基于树分类器整体性能最优的SVM二叉树层次分类方法。实验表明,该方法对比传统一类对余类法和成对分类法在整体分类精度和训练时间上都有明显提高。     

结合SVM和KNN实现求解大规模复杂问题的分治算法

针对于使用支持向量机求解大规模复杂问题存在训练时间过长和分类精度不高等困难,本文提出了一种结合支持向量机(SvM)和K-最近邻(KNN)分类的分治算法.首先对支持向量机分类机理进行分析可以得出它作为分类器实际相当于每类只选一个代表点的最近邻分类器.在此基础上,根据分治算法的基本思想将训练集划分为多个训练子集,用每个子集单独训练一个SVM,这样每个训练子集由训练后的SVM可以分别得到正例和反例的一个代表点,由这些代表点的全体构成了整个训练集的正例和反例代表点的集合,然后在这个代表点集合基础上使用KNN分类器最为整个问题的解.实验结果表明该分治算法对于大规模数据可使训练时间大幅度下降且使分类精度不同程度提高.     

基于半监督高斯混合模型核的支持向量机分类算法

提出了一种基于高斯混合模型核的半监督支持向量机(SVM)分类算法.通过构造高斯混合模型核SVM分类器提供未标示样本信息,使得SVM算法在学习标示样本信息的同时,能够兼顾整个训练样本集合的聚类假设.实验部分将该算法同传统SVM算法、直推式支持向量机(TSVM)以及随机游走(RW)半监督算法进行分类性能比较,结果证明该算法在拥有较少标示样本训练的情况下分类性能也有所提高且具有较高的鲁棒性.     

一种新的分裂层次聚类SVM 多值分类器

提出一种分裂层次聚类SVM分类树分类方法.该方法通过融合模糊聚类技术和支持向量机算法,利用分裂的层次聚类策略,有选择地重新构造学习样本集和SVM子分类器,得到了一种树形多值分类器.研究结果表明,对于k类别模式识别问题,该方法只需构造k-1个SVM子分类器,克服了SVM子分类器过多以及存在不可区分区域的缺点,具有良好的分类性能.实验结果验证了该方法的优越性.     

决策树支持向量机多分类器设计的向量投影法

针对如何有效地设计决策树支持向量机(SVM)多类分类器的层次结构这个关键问题,提出一种基于向量投影的类间可分性测度的设计方法,并给出一种基于该类间可分性测度设计决策树SVM多分类器层次结构的方法.为加快每个SVM子分类器的训练速度且保持其高推广性,将基于向量投影的支持向量预选取方法用于每个子分类器的训练中.通过对3个大规模数据集和手写体数字识别的仿真实验表明,新方法能有效地提高决策树SVM多类分类器的分类精度和速度.     

基于改进型人工鱼群算法的支持向量机参数优化

支持向量机在高维度、小样本情况下具有独特优势,但同时支持向量机的参数优化极大制约了其分类效果,目前参数优化缺乏系统的理论指导;针对传统DAG-SVM训练分类器较多,训练耗时长,分类效果受到结构排序的影响,提出了一种基于“1 vs R”策略的改进型算法;针对 SVM传统参数优化方式耗时大,优化精度不高,提出了改进型人工鱼群算法;最后结合1 vs R-DAG支持向量机算法与改进型人工鱼群算法,得到一种新的改进型支持向量机算法;仿真对比实验证实,对支持向量机的参数优化是有效可行的。     

基于对支持向量机的多类分类算法在入侵检测中的应用

针对基于传统支持向量机(SVM)的多类分类算法在处理大规模数据时训练速度上存在的弱势,提出了一种基于对支持向量机(TWSVM)的多类分类算法。该算法结合二叉树SVM多类分类思想,通过在二叉树节点处构造基于TWSVM的分类器来达到分类目的。为减少二叉树SVM的误差累积,算法分类前首先通过聚类算法得到各类的聚类中心,通过比较各聚类中心之间的距离来衡量样本的差异以决定二叉树节点处类别的分离顺序,最后将算法用于网络入侵检测。实验结果表明,该算法不仅保持了较高的检测精度,在训练速度上还表现了一定优势,尤其在处理稍大规模数据时,这种优势更为明显,是传统二叉树SVM多类分类算法训练速度的近两倍,为入侵检测领域大规模数据处理提供了有效参考价值。     

基于混沌粒子群优化的SVM分类器研究

支持向量机(SVM)分类器能较好地解决小样本、非线性、高维等分类问题,具有很强的实用性。然而,支持向量机训练参数的选择对其分类精度有着很大的影响。常用的支持向量机优化方法有遗传算法、粒子群算法都存在易陷入局部极值,优化效果较差的不足。为解决上述问题在粒子群优化算法中引入混沌思想,提出了基于混沌粒子群优化算法(CPSO)的SVM分类器优化方法,CPSO算法能提高种群的多样性和粒子搜索的遍历性,从而有效地提高了PSO算法的收敛速度和精度,更好的优化SVM分类器。并以网络异常入侵检测为研究对象进行仿真,实验结果表明,根据混沌粒子群优化的SVM分类器比传统算法优化的SVM分类器的精度高,速度快。     

基于元学习和叠加法的双层支持向量机算法

提出一种模式识别算法——双层支持量机算法,用来提高表面肌电识别精度。该算法融合集成学习中元学习的并行方法和叠加法的递进思想,把基本SVM分类器并行分布在第1层,第1层的预测结果作为第2层的输入,由第2层再进行分类识别,从而通过多层分类器组合来融合多源特征。以手臂表面肌电数据集为测试数据,采用文中的双层支持向量机,各肌肉的肌电信号分别输入基支持向量机,组合器融合各肌肉电信号特征,集成识别前臂肌肉群的肌电信号,从而实现运动意图的精确识别。实验结果显示,在预测精度上,此算法优于单个SVM分类器。在预测性能上(识别精度、耗时、鲁棒性),此算法优于随机森林和旋转森林等集成分类器。     

一种高准确度多分类结构选择方法

支持向量机SVM是目前最流行的二分类算法之一。现实生活中数据集大多要求能够进行多分类,而有向无环图DAG方法是将SVM应用扩展到多分类的用得最多的方式之一,它调用分类器次数较少,执行速度快,但是由于有错误向下累积和分类偏向性等情况存在,会影响DAG分类结果的准确度。在使用DAG-SVM的时候,对于k种类别有k!种不同的备选结构,根据数据集特性选择合适的DAG结构能够有效提高结果的准确度。提出使用估计准确度的方法,从备选结构中用穷举法选择出最高准确度估计值的DAG结构,以此作为测试集的结构进行分类。实验结果表明,相较其它方法,测试数据集采用该方法选择的DAG结构后的分类准确性得到显著提高,在对类别数量不太多的数据集进行多类分类时有较好的效果。     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

Call for Papers The 6^th International Conference on Grid and Cooperative Computing

Recent years have seen rapid advances in various grid-related technologies, middleware, and applications. The GCC conference has become one of the largest scientific events worldwide in grid and cooperative computing. The 6th international conference on grid and cooperative computing (GCC2007) Sponsored by China Computer Federation (CCF),Institute of Computing Technology, Chinese Academy of Sciences (ICT) and Xinjiang University ,and in Cooperation with IEEE Computer Soceity ,is to be held from August 16 to 18, 2007 in Urumchi, Xinjiang, China.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.     

The Distributed Time-Triggered Simulation Scheme: Core Principles and Supporting Execution Engine

Distributed real-time simulation is a young technology field but its practice is under increasing demands. In recent years the author and his collaborators have been establishing a new approach called the distributed time-triggered simulation (DTS) scheme which is conceptually simple and easy to use but widely applicable. The concept was initiated in the course of developing a new-generation object-oriented real-time programming scheme called the time-triggered message-triggered object (TMO) programming scheme. Some fundamental issues inherent in distributed real-time simulation that were learned during recent experimental studies are discussed along with some approaches for resolving the issues. An execution engine developed to support both the TMOs engaged in control computation and the TMOs engaged in DTS is also discussed along with its possible extensions that will enable significantly larger-scale DTSs.     

Software-Konfigurationsmanagement in großen Softwareprojekten

Zusammenfassung Mit zunehmender Größe der Softwaresysteme verschärfen sich die für die Software-Herstellung typischen Probleme: Beherrschen großer Objektmengen, Erhalten der Systemkonsistenz, Kontrolle der ständigen Änderungseinflüsse und Gewährleisten einer langen Lebensdauer. Die Disziplin Konfigurationsmanagement bildet den methodischen Ansatz, diese Probleme besser zu beherrschen. Software-Konfigurationsmanagement faßt die Herstellung von Softwaresystemen als eine Abfolge von kontrollierten Änderungen an gesicherten Zwischen- und Endergebnissen auf. Dargestellt werden die Objekte und Funktionen des Software-Konfigurationsmanagements sowie die hierfür in großen Software-Projekten benötigten Methoden, Instanzen und Hilfsmittel.     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and     

Editorial:Brain-machine interface(BMI) and cyborg intelligence

正Brain-machine interfaces(BMIs)aim at building a direct communication pathway between the brain and an external device,and represent an area of research where significant progress has been made during the past decade.Based on BMIs,mind information can be read out by neural signals to control     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate     

SCIENCE CHINA Information Sciences SUBJECT INDEX TO VOLUME 57(2014)

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