基于粗糙集的加权朴素贝叶斯邮件过滤方法

邮件过滤中有两个关键问题,一是如何选择有效的邮件特征集,二是设计较好的邮件过滤算法。在对邮件特性进行分析的基础上,综合邮件头及邮件内容的主要形象特征给出了一种新的邮件特征集提取方法。用粗糙集的信息观点度量了各属性的重要性,并以此为权重进行加权朴素贝叶斯垃圾邮件过滤,有效地解决了朴素贝叶斯分类中的条件依赖性问题。通过在中英文邮件集上的测试实验,证明了所提出的邮件过滤方法的有效性。     

网上虚拟教室中笔记系统的设计与实现

随着计算机网络的发展,网上教学成为当今计算机辅助教育的研究热点,而对于一个完善的网上虚拟教室系统,笔记系统是不可缺少的。文章着重论述了利用JAVA及JDBC对笔记系统的设计与实现,并提出了利用人工智能领域中的不确定推理等知识,根据学生感兴趣的主题词,主动进行信息获取服务。     

MODEEP: a motion-based object detection and pose estimation method for airborne FLIR sequences

In this paper, we present a method called MODEEP (Motion-based Object DEtection and Estimation of Pose) to detect independently moving objects (IMOs) in forward-looking infrared (FLIR) image sequences taken from an airborne, moving platform. Ego-motion effects are removed through a robust multi-scale affine image registration process. Thereafter, areas with residual motion indicate potential object activity. These areas are detected, refined and selected using a Bayesian classifier. The resulting regions are clustered into pairs such that each pair represents one object's front and rear end. Using motion and scene knowledge, we estimate object pose and establish a region of interest (ROI) for each pair. Edge elements within each ROI are used to segment the convex cover containing the IMO. We show detailed results on real, complex, cluttered and noisy sequences. Moreover, we outline the integration of our fast and robust system into a comprehensive automatic target recognition (ATR) and action classification system.     

基于数据挖掘方法的电子邮件过滤

电子邮件在给人们带来很多方便抽时,也产生了一个新的问题,即大量垃圾邮件的出现。邮件过滤就是从大量邮件中过滤出垃圾邮件,帮助用户寻找到所需要的有用邮件。本文介绍了一个基于数据挖掘方法的邮件过滤系统原型,给出了Bayes方法的几个基于概念,并重点讨论了要实现这个系统所需要处理的几个关键问题。     

垃圾邮件过滤技术研究与发展

电子邮件服务现已成为现代生活通信中不可缺少的一部分,也是Intemet服务的一个主要的组成部分。但是垃圾邮件的蔓延给用户带来了严重的损失．如何防范垃圾邮件具有重要的实用意义。本文简单的介绍了几种常用的邮件过滤技术并分析比较了各种技术的优缺点。     

Optimization of shell buckling incorporating Karhunen-Loève-based geometrical imperfections

The optimization of shell buckling is performed considering peak normal force and absorbed internal energy in the presence of geometrical imperfections implemented through Karhunen-Loève expansions. Initially, the mass of a shell is minimized in the presence of random initial imperfections by allowing cutouts in the material, subject to constraints on the average peak force and average internal energy. Then, robustness is considered by minimizing the coefficient of variation of the normal peak force while constraining the average peak force and average internal energy. LS-OPT® is used both to generate an experimental design and to perform a Monte Carlo simulation (96 runs) using LS-DYNA® at each of the experimental design points. The effect of imperfections when minimizing the mass is not large, but when considering robustness, however, the optimal design has a substantially increased hole size and increased shell thickness, resulting in a heavier design with maximal robustness within the constraints.     

基于DPI和机器学习的网络流量分类方法

网络流量分类是实现网络管理的重要技术之一,但是单一的基于DPI或是机器学习的分类方法分类精确度低.提出了一种基于DPI和机器学习相结合的网络流量分类方法.该方法采用DPI检测已知特征的网络流量,利用机器学习方法辅助分析未知特征以及加密的网络流.实验表明该方法能够提高网络流量分类的精确度.     

Combining classifiers under probabilistic models: experimental comparative analysis of methods

This work will present a review of the concept of classifier combination based on the combined discriminant function. We will present a Bayesian approach, in which the discriminant function assumes the role of the posterior probability. We will propose a probabilistic interpretation of expert rules and conditions of knowledge consistency for expert rules and learning sets. We will suggest how to measure the quality of learning materials and we will use the measure mentioned above for an algorithm that eliminates contradictions in the rule set. In this work several recognition algorithms will be described, based on either: (i) pure rules, or; (ii) rules together with learning sets. Furthermore, the original concept of information unification, which enables the formation of rules on the basis of learning set or learning set on the basis of rules will be proposed. The obtained conclusions will serve as a spring‐board for the formulation of new project guidelines for this type of decision‐making system. At the end, experimental results of the proposed algorithms will be presented, both from computer generated data and for a real problem from the medical diagnostics field.     

小子样状态下舰船特种阀门可靠性评估方法

针对舰船特种阀门 可靠性评估比较困难的问题,提出了将Bayes理论和相似性理论相结合的评估新方法.充分利用历史先验信息,并结合现场数据从而获得后验分布;利用相似性理论确定新旧型号阀门的相似度精确值.综合历史后验和后验分布,得到产品可靠性的融合后验.结合实例,对比分析了经典评估方法、传统Bayes方法和新方法所得到的新型号特种阀门可靠性的置信下限,验证了所提出方法的科学性和实用性.研究了新型号阀门的两参数威布尔寿命分布特性,给出了可靠度函数和可靠度寿命表达式,其计算结果可作为产品的接收判据,并在应用中提高了舰船特种阀门可靠性的评估精度,同时可以显著地减少现场试验样本数量.     

基于贝叶斯理论的武烈河水质综合评价

选取2010年武烈河6个监测断面的水质监测数据作为研究对象,采用贝叶斯公式对其水质进行综合分析评价,结果表明:各监测断面水质评价均在Ⅲ类以上,总体水质结果较好,符合水功能区划要求;66.7%的断面达到Ⅰ类,包括高寺台上游、双峰寺水库坝址、雹神庙和污水处理厂出水口下游4个断面;高寺台下游断面只达到Ⅲ级,主要是由于高寺台镇及其矿区生活污水和农业退水未经处理直接排入河道造成的。为保障双峰寺水库运行后的流域水环境质量和供水安全,需从水源地建设、点源治理和面源治理3个方面采取水环境保护措施。