概念空间中上下位关系的意义识别研究

针对上下位关系在分类层级结构建立阶段遇到的多义性问题,给出一种概念空间中上下位关系意义识别的方法.单个概念的意义识别问题被转换为概念空间中上下位关系的意义识别.首先利用并列语境解决语境稀疏问题,获取上下位关系意义的语境.然后利用<同义词词林>对每个语境进行词义修正,以三种特征计算特征词权重,构建"关系一词'的高维向量空间,然后通过潜在语义分析降维,获取上下位关系意义的潜在语义,最后组平均聚类后得到关系的意义划分.在实验中,给出了聚类阈值自动调整函数,分析了词林和潜在语义分析的作用,实验结果证实了方法的有效性.     

基于参数重要度的多元时间序列相似性查询

针对多元时间序列的相似性查询问题,给出参数重要度的定义,提出一种基于参数重要度的候选集查询方法。通过对多元时间序列的SVD分解,将奇异值向量和特征矩阵作为多元序列的特征,基于线性空间中的坐标变换原理构造2个多元时间序列的相似性度量模型,实现在候选集上的精确匹配并获得最终的结果集。对飞行数据的相似性查询实验验证了该方法的有效性。     

结构化信息的去重方法

针对载有结构化信息的网页,提出一种基于学习的去重方法。通过先期准备的样本定义分类器,根据分类器对页面中结构化信息的不同属性字段进行分类和距离计算,计算出整个信息对象和已分类样本信息的距离,以这些距离与阈值的大小关系判断该信息对象是否重复。     

基于改进灰色理论的威胁指标权重技术

针对各种网络指标之间的相互影响,同时考虑主客观2个方面的因素,提出用灰色理论中的灰关联度和传统层次分析法相结合的算法进行网络威胁指标权重的确定。实验证明,该方法数学理论严谨,具有良好的实用价值,使网络威胁评估方法在可信度方面有一定的 提高。     

基于本体的概念语义相似度度量

针对概念语义相似度度量问题,提出结合基于图理论和信息量2种方法的语义相似度度量算法。计算2个概念在概念图中连接的路径长度、局部密度以及在连接2个概念之间的路径上连接关系的连接力度,结合连结路径权重和信息量来度量概念之间的语义相似度。实验结果表明,该算法能取得较好的度量效果。     

Minimizing a linear objective function under a fuzzy max-t norm relation equation constraint

The work examines the feasibility of minimizing a linear objective function subject to a max-t fuzzy relation equation constraint, where t is a continuous/Archimedean t-norm. Conventional methods for solving this problem are significantly improved by, first separating the problem into two sub-problems according to the availability of positive coefficients. This decomposition is thus more easily handled than in previous literature. Next, based on use of the maximum solution of the constraint equation, the sub-problem with non-positive coefficients is solved and the size of the sub-problem with positive coefficients reduced as well. This step is unique among conventional methods, owing to its ability to determine as many optimal variables as possible. Additionally, several rules are developed for simplifying the remaining problem. Finally, those undecided optimal variables are obtained using the covering problem rather than the branch-and-bound methods. Three illustrative examples demonstrate that the proposed approach outperforms conventional schemes. Its potential applications are discussed as well.     

Research and Implementation of Task Management Model in Product Development Process Management

The implementation of product development process management (PDPM) is an effective means of developing products with higher quality in shorter lead time. It is argued in this paper that product, data, person and activity are basic factors in PDPM With detailed analysis of these basic factors and their relations in product developmed process, all product development activities are considered as tasks and the management of product development process is regarded as the management of task execution A task decomposition based product development model is proposed with methods of constructing task relation matrix from layer model and constraint model resulted from task decomposition. An algorithm for constructing directed task graph is given and is used in the management of tasks. Finally, the usage and limitation of the proposed PDPM model is given with further work proposed.     

基于PROFIBUS的经济型现场总线控制系统

介绍了PROFIBUS的体系结构、通信协议及基于PROFIBUS、PC、PLC实现的现场总线控制系统。本文郑重讨论PROFIBUS－FMS的特性、功能及其应用。     

Modeling of the Electrostatic (Plasmon) Resonances in Metallic and Semiconductor Nanoparticles

Plasmon (electrostatic) resonances are treated as an eigenvalue problem for specific boundary integral equation. This leads to direct calculation of resonance values of permittivity and resonance frequency. The technique is illustrated by numerical examples of calculation of resonance frequencies for 3D nanoparticles.     

D-Index: Distance Searching Index for Metric Data Sets

In order to speedup retrieval in large collections of data, index structures partition the data into subsets so that query requests can be evaluated without examining the entire collection. As the complexity of modern data types grows, metric spaces have become a popular paradigm for similarity retrieval. We propose a new index structure, called D-Index, that combines a novel clustering technique and the pivot-based distance searching strategy to speed up execution of similarity range and nearest neighbor queries for large files with objects stored in disk memories. We have qualitatively analyzed D-Index and verified its properties on actual implementation. We have also compared D-Index with other index structures and demonstrated its superiority on several real-life data sets. Contrary to tree organizations, the D-Index structure is suitable for dynamic environments with a high rate of delete/insert operations.