基于C4.5决策树的流量分类方法

近年来,利用机器学习方法处理流量分类问题成为网络测量领域一个新兴的研究方向.在现有研究中,朴素贝叶斯方法及其改进算法以其实现简单、分类高效的特点而被广泛应用.但此类方法过分依赖于样本在样本空间的分布,具有潜在的不稳定性.为此,引入C4.5决策树方法来处理流量分类问题.该方法利用训练数据集中的信息熵来构建分类模型,并通过对分类模型的简单查找来完成未知网络流样本的分类.理论分析和实验结果都表明,利用C4.5决策树来处理流量分类问题在分类稳定性上均具有明显的优势.     

基于决策树模型的P2P流量分类方法

P2P流量逐渐成为互联网流量的重要组成部分,精确分类P2P流量对于有效管理网络和合理利用网络资源都具有重要意义。近年来,利用机器学习方法处理P2P流量分类问题已成为流量识别领域的一个新兴研究方向。利用决策树中的C4.5算法和P2P流量的特征属性来构建决策树模型,进而完成P2P流量分类问题。实验结果表明,基于决策树模型的方法能有效避免P2P网络流分布变化所带来的不稳定性;与SVM（support vector machine,支持向量机）、NBK（nave Bayes using kernel densi     

基于决策树的P2P流量识别方法研究

针对新型P2P业务采用净荷加密和伪装端口等方法来逃避检测的问题,提出了一种基于决策树的P2P流量识别方法.该方法将决策树方法应用于网络流量识别领域,以适应网络流量的识别要求.决策树方法通过利用训练数据集中的信息熵来构建分类模型,并通过对分类模型的简单查找来完成未知网络流样本的分类.实验结果验证了C4.5决策树算法相比较Na(i)ve Bayes、Bayes Network算法,处理相对简单且计算量不大,具有较高的数据处理效率和分类精度,能够提高网络流量分类精度,更适用于P2P流量识别.     

基于支持向量机的Internet流量分类研究

准确的网络流量分类是众多网络研究工作的基础,也一直是网络测量领域的研究热点.近年来,利用机器学习方法处理流量分类问题成为了该领域一个新兴的研究方向.在目前研究中应用较多的是朴素贝叶斯(naive Bayes,NB)及其改进算法.这些方法具有实现简单、分类高效的特点.但该方法过分依赖于样本空间的分布,具有内在的不稳定性.因此,提出一种基于支持向量机(sulbport vector machine,SVM)的流量分类方法.该方法利用非线性变换和结构风险最小化(structural risk minimization,SRM)原则将流量分类问题转化为二次寻优问题,具有良好的分类准确率和稳定性.在理论分析的基础上,通过在实际网络流集合上与朴素贝叶斯算法的对比实验,可以看出使用支持向量机方法处理流量分类问题,具有以下3个优势:1)网络流属性不必满足条件独立假设,无须进行属性过滤;2)能够在先验知识相对不足的情况下,仍保持较高的分类准确率;3)不依赖于样本空间的分布,具有较好的分类稳定性.     

天地一体化智能网络流量实时分类

天地一体化智能网络规模大,环境复杂,网络中流量业务类型繁多且流量具有突发性.本文结合Spark大数据分布式平台,根据流量的特点设计了SFFS-FCBF-C4.5(简称SFC)决策树分类模型,实现了大规模网络下流量的实时分类,以保障网络中资源的合理分配和利用.SFC算法是在C4.5决策树算法的基础上结合了改进后的快速相关滤波算法(Fast Correlation-Based Filter Solution, FCBF)和连续型属性值离散化算法,可以在有效去除冗余特征和降低模型复杂度的同时,提高模型分类的速度和准确率.仿真结果表明,SFC决策树分类模型相比传统的流量分类模型具有较好的稳定性和较高的准确率,可以很好的适应复杂多变的网络环境.同时,Spark大数据分布式平台的应用大幅度提高了大规模网络下流量分类的速度,能够对海量流量进行实时分类.     

基于距离权值的C4.5组合决策树算法

针对C4.5决策树算法在处理多维数据分类时,没有考虑各属性对分类结果的影响,导致分类准确率低的问题,提出一种基于距离权值的C4.5组合决策树算法。根据标准欧式距离定义数据属性的距离权值,更新C4.5决策树算法的信息增益率,得到基于距离权值的C4.5算法。利用改进后的C4.5决策树分类算法训练多个基分类器,基分类器通过Bagging集成方法构建组合决策树。实验结果表明,该算法在处理多维数据时有较高的准确性和稳定性。     

分类不平衡协议流的机器学习算法评估与比较

网络协议流不平衡环境下,流样本分布的变化对基于机器学习的流量分类器准确性及稳定性有较大的影响选择合适的机器学习算法以适应网络协议流不平衡环境下的在线流量分类,显得格外重要.为此,首先通过单因子实验设计,验证了C4.5决策树、贝叶斯核估计(NBK)和支持向量机(SVM)这3种分类算法统计TCP连接开始的前4个数据包足以分类流量.接着,比较了上述3种分类算法的性能,发现C4.5决策树的测试时间最短,SVM分类算法最稳定.然后,将Bagging算法应用到流量分类中.实验结果表明,Bagging分类算法的稳定性与SVM相似,且测试时间与建模时间接近于C4.5决策树,因此更适于在线分类流量.     

基于贝叶斯方法的决策树分类算法

针对数据挖掘的特点和本质,充分利用贝叶斯方法和决策树分类的优点,将贝叶斯的先验信息方法与决策树分类的信息增益方法相结合,提出了一种新的数据挖掘分类算法(BD1.0算法),并对此算法进行了设计和分析。实验分析表明,该算法可以处理不一致或者不完整数据等“脏数据”,比单纯使用贝叶斯方法或决策树方法具有更高的准确率,而且与C4.5算法具有近似的时间复杂度。     

基于贝叶斯网络分类器的产品故障率分类研究*

针对装备在不同配置及使用环境的条件下运行的故障率等级差异,详细介绍并分析了现有各贝叶斯分类器的特点和构建算法。在此基础上,提出了基于贝叶斯网络的产品故障分类模型建模方法用于指导实际分类任务的模型建立和应用。通过法国某装备生产企业的实例分析,实验结果证明在所有的贝叶斯网络分类器及传统的决策树C4.5分类器中,树型朴素贝叶斯分类器能够取得最好的分类效果,并为后续的维修资源配置及产品运行能力优化提供有效的理论支持。     

入侵检测分类技术的比较研究

入侵检测是网络安全研究的主要问题之一,有效的检测方法在开发入侵检测系统中发挥着至关重要的作用。通过对数据挖掘中的分类算法进行深入研究,选取四种常用的分类算法如决策树、贝叶斯、K最近邻法和神经网络来分别构建入侵检测系统,旨在找到最有效的分类算法。仿真实验在Weka环境下使用KDD CUP99数据集进行测试。实验表明,采用C4.5决策树构建的入侵检测系统具有良好的检测性能,是一种非常有效的网络入侵检测方法。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

基于QTE的蒙古文显示机制研究与实现

蒙古语言是中国蒙古族使用的通用语言,由于蒙古文区别于其他文字的书写方式和其自身变形机制等特点,在很多通用的文字处理引擎中都不被支持。在嵌入式产品开发与应用领域中Linux加QTE已经成为流行方式。该文给出了一种在QTE环境上实现基于标准Unicode的蒙古文点阵显示和变形算法, 并自定义了支持蒙古文的QTE组件,扩展了QTE功能,为在Linux加QTE方式的嵌入式体系结构中处理蒙古文提供了一种解决方法。