一类不完全信息线性规划方法

本文建立了基于不完全信息的模糊数系数线性规划模型，提出了模糊优值的概念、数学定义和求解方法，并且给出了最优值关于系数连续性的几个结果。     

粗糙集在不完备信息系统中的一种扩充方法

对于不完备信息系统,通过引入一种标准化的距离函数和相容阈值,提出了一种相容关系,给出了基于相容关系的上下近似的定义,讨论了相容阈值的取值。     

用于不完全信息数据库的多值逻辑研究

1引言 自20世纪70年代末以来,用多值逻辑处理空值问题已成为数据库理论的一个重要研究方向[1～3].不完全信息数据库中引入多值逻辑(MVL)的研究是和空值的语义有关的.数据库中引起信息缺失的原因有十几种,根据语义可分成三种类型:不存在型空值、存在型空值和占位型空值.若在空值的处理中,这三种解释都采用,不作简化,这将导致七值逻辑(7VL).     

一种不完全信息下的多智能体协作机制

在分布式多智能体系统中,由于agen嗵常具有不完全信息,因此大大影响了系统的协作效果。该文采用博弈论和决策理论相结合的方法,将不完全信息下的agcnt协作转换成完全信息下agent协作问题来求解,提出了一种不完全信息下的agent协作机制。     

粗糙集理论在处理不完全信息的应用

对不完全信息的处理相对于完全信息来说是一个比较难的问题。在过去几年里,已经提出了几种处理不完全信息的方法。本文在前人研究的基础上,进一步提出了一种利用粗糙集理论处理不完全信息的方法,该方法不仅能够对不完全信息系统进行属性约简,并且能够在此基础上对最简属性集中包含的不确定信息进行进一步的处理。     

Ontological Approach for Information Discovery in Internet Databases

The Internet has solved the age-old problem of network connectivity and thus enabling the potential access to, and data sharing among large numbers of databases. However, enabling users to discover useful information requires an adequate metadata infrastructure that must scale with the diversity and dynamism of both users' interests and Internet accessible databases. In this paper, we present a model that partitions the information space into a distributed, highly specialized domain ontologies. We also introduce inter-ontology relationships to cater for user-based interests across ontologies defined over Internet databases. We also describe an architecture that implements these two fundamental constructs over Internet databases. The aim of the proposed model and architecture is to eventually facilitate data discovery and sharing for Internet databases.     

一种基于RDBMS的XML数据的存储方法

XML作为一种数据交换的标准在互联网上推出,使得XML数据和数据库的相互交换成为必要:一是因为WEB中大量的多样化数据需要进行有效的存储和管理;二是因为在现有的数据库中存储有大量的数据并且需要将这些数据转换为XML发布到WEB中。论文提出了一个基于关系数据库的数据转换框架,基于数据的完整性讨论XML数据存储策略。建立一个XML通用数据模型,把文档树分解成多个节点,根据一定的映射规则存储到关系表中,从而不用考虑文档的模式信息(DTD、XMLSchema)。最后通过一个具体的文档实例来说明这种策略的有效性。     

基于粗糙集方法的不完备信息系统的知识推理

含空值决策表的分析一直是智能信息处理领域的一个难点,论文讨论基于赋值容差关系的数据不完全的信息系统中的数据处理方法,并用实例说明不完全决策表中属性约简和决策规则的发现方法。     

一种从不完备关系数据中学习PRM的方法

现有的关系学习研究都是基于完备数据进行的,而现实问题中,数据通常是不完备的.提出一种从不完备关系数据中学习概率关系模型(probabilistic relational models,简称PRMs)的方法——MLTEC(maximum likelihood tree and evolutionary computing method).首先,随机填充不完备关系数据得到完备关系数据.然后从每个随机填充后的数据样本中分别生成最大似然树并作为初始PRM网络,再利用进化过程中最好的网络结构反复修正不完备数据集,最后得到概率关系模型.实验结果显示,MLTEC方法能够从不完备关系数据中学习到较好的概率关系模型.     

Remote Access to Multimedia Databases: An Object Oriented Approach

Recent advances in media processing technology have resulted in the generation of vast amounts of multimedia information. There exists a need to manage this information. This paper describes the design and implementation of an object-oriented system used for remote multimedia database access. The work includes the design of a framework to model multimedia information in the object-oriented database POET, the development of a POET multimedia server to provide access to this information and the design of client interfaces to the system.     

An Interface Agent Approach to Personalize Users' Interaction with Databases

Making queries to a database system through a computer application can become a repetitive and time-consuming task for those users who generally make similar queries to get the information they need to work with. We believe that interface agents could help these users by personalizing the query-making and information retrieval tasks. Interface agents are characterized by their ability to learn users' interests in a given domain and to help them by making suggestions or by executing tasks on their behalf. Having this purpose in mind we have developed an agent, named QueryGuesser, to assist users of computer applications in which retrieving information from a database is a key task. This agent observes a user's behavior while he is working with the database and builds the user's profile. Then, QueryGuesser uses this profile to suggest the execution of queries according to the user's habits and interests, and to provide the user information relevant to him by making time-demanding queries in advance or by monitoring the events and operations occurring in the database system. In this way, the interaction between database users and databases becomes personalized while it is enhanced.     

一种信息不完全确定的多准则分类决策方法

针对准则权系数信息不完全确定和准则值信息不完全且有训练集的多准则分类决策问题,提出一种基于证据推理的分类方法,该方法在对训练集分类的基础上,结合不完全确定的准则权系数信息等建立非线性规划模型;然后利用遗传算法和单纯形法联合求解优化模型,得出准则权系数和分类效用阈值等参数,进而求出每一方案的效用值;最后与分类的效用阈值进行比较,得到方案集的分类．应用实例说明了该方法的有效性和可行性。     

一种静态分析C^＋＋异常处理的方法

异常处理是现代程序设计语言提供的用来提高软件健壮性的一种机制。由于在C^＋＋的函数界面中并不要求声明该函数所能传播出的异常的类型，所以要想提高系统的健壮性，必须清楚在程序的执行过程中可能引发的异常、异常的传播路径等。然而在大型系统中，要想确定这些信息是非常困难的。本文针对C^＋＋的异常处理机制，首先提出了一个描述C^＋＋异常结构信息的模型，并把该模型应用于递归函数中。然后，描述了一个基于该模型的分析C^＋＋程序异常结构信息的工具CETool。该工具能提供所有显式引发异常的有关信息，为系统中异常处理结构的改进和程序的结构测试提供有价值的信息。最后给出了该工具的实现方法和应用实例。     

An XML-Based Approach to Publishing and Querying the History of Databases

There is much current interest in publishing and viewing databases as XML documents. The general benefits of this approach follow from the popularity of XML and the tool set available for visualizing and processing information encoded in this universal standard. In this paper, we explore the additional and unique benefits achieved by this approach on temporal database applications. We show that XML with XQuery can provide surprisingly effective solutions to the problem of supporting historical queries on past content of database relations and their evolution. Indeed, using XML, the histories of database relations can be naturally represented by temporally grouped data models. Thus, we identify mappings from relations to XML that are most conducive to modeling and querying database histories, and show that temporal queries that would be difficult to express in SQL can be easily expressed in standard XQuery. This approach is very general, insofar as it can be used to store the version history of arbitrary documents and, for relational databases, it also supports queries on the evolution of their schema. Then, we turn to the problem of supporting efficiently the storage and the querying of relational table histories. We present an experimental study of the pros and cons of using native XML databases, versus using traditional databases, where the XML-represented histories are supported as views on the historical tables.     

An Agent‐Based Pythagorean Fuzzy Approach for Demand Analysis with Incomplete Information

Analyzing demand in environments with incomplete information is a challenging task. This paper proposes a novel agent‐based Pythagorean fuzzy approach for analyzing this kind of demand. First, a Bayesian game is described with a large number of finite players, and this is followed by a Pythagorean fuzzy‐based decision mechanism. Unlike the classical methods in the literature, the proposed method in this paper neither assumes nor forecasts the demand in a system. Instead, it tries to analyze the demand when there is limited availability of input data, or processing data are computationally expensive. The study ends with an application of the proposed system to an electricity grid. Electricity prices used as an incentive to construct an agent‐based system that efficiently reduces the peak amounts in a smart grid by analyzing the demand. Test results provide evidence that the proposed approach is promising to design demand response systems.     

一种信息系统集成方法

传统的信息系统之间缺乏很好的信息共享机制,成为一个个孤立的信息“烟囱”,无法提供面向全局的服务。为解决这个问题,本文提出了在已有的自治信息系统基础上,构造松散耦合分布式信息系统的方法及系统的体系结构,并用Petri网建立了系统的模型,为对系统进行分析和验证打下了理论基础。     

一种在无标注图像库中进行的基于关键词的检索方法

提出一种在无标注图像库中进行的基于关键词的检索方法.该方法在用户输入关键词后,首先利用图像周围的文字信息从网页中过滤一部分与检索主题无关的图像.然后利用图像的视觉特征在之前的基础上筛选出与检索词具有高度相关性的图像.最后利用数据审计技术对筛选出的图像进行进一步精化,并利用精化后的图像对图像库进行检索.实验结果表明,借助数据审计技术,该方法可有效提高对无标注图像库进行基于关键词的检索性能.