基于双字词的动态最大匹配分词算法的研究

通过研究和分析现有最大匹配分词算法，词库结构的设计和分词算法直接关系着分词的速度和效率，提出了一种改进的最大匹配分词算法——基于双字词的动态最大匹配分词算法，设计并实现了汉语分词词库和算法。实验结果表明，此算法相对于现有最大匹配分词算法有显著提高。     

面向概念设计的专利知识挖掘方法研究

研究了概念设计知识空间层次结构体系,分析了专利知识空间与已有设计知识空间之间的关系,说明了专利知识挖掘具有扩展设计知识空间、避免重复设计和促进产品创新的作用.提出了一种面向概念设计的专利知识挖掘方法,建立了统一的专利技术特征表示模型,利用词法分析、句法分析、语义分析等自然语言理解技术,抽取专利技术特征信息,通过不同层次的知识挖掘形成专利知识空间.以钻夹头产品设计为例,采用该方法挖掘相同设计领域的产品专利需求知识和功能知识,辅助产品的需求分析和功能结构变异,设计结果表明,该方法充分利用了专利资源,为概念设计提供丰富的设计知识,有效地提高了产品创新能力.     

基于一维云模型的交通信息预测算法

云模型是对语言值所蕴含的模糊性和随机性的一种数学描述，它用期望值、熵和超熵表征定性概念，将概念的模糊性和随机性集成在一起，能够实现定量与定性之间的相互转换，因而对交通信息的高度不确定性具有很强的鲁棒性．基于云模型提出的预测机制在一定程度上有效地解决了交通信息存在的模糊性和随机性问题，为交通信息预测提供了一种新的方法．检验结果表明预测值基本上与实际值吻合．     

基于Hash函数的脆弱图像水印算法

为了增强水印的内容认证性,提出了一种适用于数字媒体产品内容篡改证明和完整性认证的脆弱水印算法.采用Hash函数加密生成基于图像内容的脆弱水印,并将其嵌入到随机选择的图像点的LSB(1east significant bit),有效地抵抗了伪认证攻击.利用Hash函数Hamming重量对输入变化的敏感性,能够精确地定位对加入水印图像的篡改,并且水印提取不需要原始图像.实验结果表明该脆弱水印算法具有较好的篡改定位能力.     

基于双向匹配法和特征选择算法的中文分词技术研究

传统的双向匹配算法虽然能够发现歧义现象,但是却不能解决歧义问题.为了更好地进行歧义消解,提出了一种基于双向匹配法和特征选择算法的中文分词技术,通过积累的语料库,设计并实现了一个基于两种方法的分词系统.该系统的实验结果表明,基于双向匹配法和特征选择算法的中文分词技术比传统方法的效果要好.     

基于一维云模型的交通信息预测算法

云模型是对语言值所蕴含的模糊性和随机性的一种数学描述，它用期望值、熵和超熵表征定性概念，将概念的模糊性和随机性集成在一起,能够实现定量与定性之间的相互转换，因而对交通信息的高度不确定性具有很强的鲁棒性. 基于云模型提出的预测机制在一定程度上有效地解决了交通信息存在的模糊性和随机性问题， 为交通信息预测提供了一种新的方法.检验结果表明，预测值基本上与实际值吻合.     

改进M-D结构的二次多变量Hash算法

针对传统Hash算法有安全缺陷的问题,利用有限域上多变量二次方程组求解(MQ)问题的困难性,设计了一种新的基于有限域上多变量二次多项式的Hash算法.新算法给出了一个改进的M-D结构,采用了NMAC(nested MAC)的 思想,并加入了计数器,旨在抵抗一些针对传统M-D结构的攻击.新算法具有可调的输出参数,可以适应...     

自然语言理解的全信息方法论

在经济全球化需求的推动下,世界在酝酿一场“自然语言信息技术革命” ,它的基础和核心是“自然语言理解”的理论与方法. “全信息自然语言理解方法论”是作者的“全信息理论”在自然语言理解领域的应用. 与文献中已有的其他工作不同,其主要特色是: 一方面,试图实现语法信息、语义信息、语用信息的综合利用;另一方面寻求“规则方法”和“统计方法”的和谐互补,从而有效增强对自然语言的理解能力. 近几年来,应用这一方法论完成了一系列自然语言理解方面的课题,取得了一批可喜的研究成果,表明全信息自然语言理解方法论具有很好的前景.     

基于文本的信息隐藏算法研究

提出了一种基于文本的信息隐藏算法,利用格式文档的特点,对文档进行字分类和节分类,然后通过字体变换,文本颜色变换等多种变换方法达到隐藏密文信息的目的。实验结果表明这一算法具有较好的隐藏效果,具有一定的抗攻击能力,从而使其鲁棒性有所提高。     

基于Hash算法的DNA序列k-mer index问题的数学建模

针对查找DNA序列的相似序列问题,给出了建立索引和查找索引的数学模型,基于Hash算法,建立了依赖于k值大小的顺序索引模型和散列索引模型,特别对较大k值选用了DJBHash函数,有效的避免了Hash冲突问题。最后在硬件平台CPU为2.6GHz、内存为8G、操作系统为64位Windows 7的条件下,对100万条长度为100的DNA序列进行了测试,给出了不同k值下建立和查询索引的用时和占用内存情况,有效的解决了DNA序列的k-mer index问题。     

城市道路交通系统多信息平台的融合技术分析

分析了我国城市道路交通信息系统的发展现状及发展目标,研究了城市道路交通信息系统中多信息平台融合的3种模式,并对多信息平台互联中的关键技术进行了探讨.指出两级网络结构的多信息平台组网方式较适合我国目前的城市道路交通信息系统发展现状.     

一种基于车间通信的交通信息采集方法

为了及时、准确地获取城市道路交通信息,提出了一种基于车间通信的交通信息采集方法,将具有车间通信功能的车辆视为路网中的移动传感器节点;路旁基站通过对节点采集到的交通数据进行分析,得到路段实时交通状态。另外,还设计了基于上述方法的无线交通信息服务系统(WTISS)原型,同时结合Paramics、NS2、Matlab、MySQL等工具完成了WTISS仿真系统,并在该仿真系统上验证了本文方法的正确性。     

Effects of real-time traffic information systems on traffic performance under different network structures

The effects of real-time traffic information system (RTTIS) on traffic performance under parallel, grid and ring networks were investigated. The simulation results show that the effects of the proportion of RTTIS usage depend on the road network structures. For traffic on a parallel network, the performance of groups with and without RTTIS level is improved when the proportion of vehicles using RTTIS is greater than 0 and less than 30%, and a proportion of RTTIS usage higher than 90% would actually deteriorate the performance. For both grid and ring networks, a higher proportion of RTTIS usage always improves the performance of groups with and without RTTIS. For all three network structures, vehicles without RTTIS benefit from some proportion of RTTIS usage in a system.     

决策树学习算法在交通方式选择模型中的应用

主要阐述了决策树学习算法在交通方式选择模型中的应用.在基本决策树的基础上,使用随机森林组合学习算法来建立交通方式选择模型,以Bagging预测方法和CART算法为主,以随机特征选择和"投票"方法为辅,并相互融合,结合具体实例详细介绍该模型的建立,从数据的选择到整个森林中树的数目和每个结点处抽取的候选属性的个数调整,并对模型进行了相应的评估.实验结果表明,随机森林预测精度高,且对噪声数据具有较强的稳健性,采用决策树学习算法得出的规则在交通方式选择的分析中具有较好的实用价值.     

Feature selection algorithm for text classification based on improved mutual information

In order to solve the poor performance in text classification when using traditional formula of mutual information (MI),a feature selection algorithm were proposed based on improved mutual information.The improved mutual information algorithm,which is on the basis of traditional improved mutual information methods that enhance the MI value of negative characteristics and feature’s frequency,supports the concept of concentration degree and dispersion degree.In accordance with the concept of concentration degree and dispersion degree,formulas which embody concentration degree and dispersion degree were constructed and the improved mutual information was implemented based on these.In this paper,the feature selection algorithm was applied based on improved mutual information to a text classifier based on Biomimetic Pattern Recognition and it was compared with several other feature selection methods.The experimental results showed that the improved mutual information feature selection method greatly enhances the performance compared with traditional mutual information feature selection methods and the performance is better than that of information gain.Through the introduction of the concept of concentration degree and dispersion degree,the improved mutual information feature selection method greatly improves the performance of text classification system.     

Road traffic states estimation algorithm based on matching of regional traffic attracters

To effectively solve the traffic data problems such as data invalidation in the process of the acquisition of road traffic states, a road traffic states estimation algorithm based on matching of the regional traffic attracters was proposed in this work. First of all, the road traffic running states were divided into several different modes. The concept of the regional traffic attracters of the target link was put forward for effective matching. Then, the reference sequences of characteristics of traffic running states with the contents of the target link＇s traffic running states and regional traffic attracters under different modes were established. In addition, the current and historical regional traffic attracters of the target link were matched through certain matching rules, and the historical traffic running states of the target link corresponding to the optimal matching were selected as the initial recovery data, which were processed with Kalman filter to obtain the final recovery data. Finally, some typical expressways in Beijing were adopted for the verification of this road traffic states estimation algorithm. The results prove that this traffic states estimation approach based on matching of the regional traffic attracters is feasible and can achieve a high accuracy.     

高速公路交通流量信息系统

交通流量信息在高速公路的规划、建设与管理工作中,起着十分重要的作用．高速公路交通流量信息系统以ＯＤ流量为基础,利用现代计算机技术,实现了交通流量信息处理的自动化,极大地提高了交通流量信息处理的及时性、准确性与全面性．介绍了系统的功能,特点,并对应用的意义进行了论述．     

Real-time traffic information extraction based on compressed video with interframe motion vector

Extraction of traffic information from image or video sequence is a hot research topic in intelligent transportation system and computer vision. A real-time traffic information extraction method based on compressed video with interframe motion vectors for speed, density and flow detection, has been proposed for extraction of traffic information under fixed camera setting and well-defined environment. The motion vectors are first separated from the compressed video streams, and then filtered to eliminate incorrect and noisy vectors using the well-defined environmental knowledge. By applying the projective transform and using the filtered motion vectors, speed can be calculated from motion vector statistics, density can be estimated using the motion vector occupancy, and flow can be detected using the combination of speed and density. The embodiment of a prototype system for sky camera traffic monitoring using the MPEG video has been implemented, and experimental results proved the effectiveness of the me