基于粗糙集和模糊集的属性约简算法

粗糙集理论和模糊集理论都是用来处理不完整和不确定信息的理论,两者都可用来观察、测试数据并进行推理。虽然它们之间有一些重叠,但两者的着眼点和计算方法是不一样的,因此不能相互替代,而是必须结合起来使用。本文在研究粗糙集和模糊集理论的基础上将两者相结合,提出了一个新的属性约简算法,并给出了一个应用实例。     

缺省理论的简化

缺省理论△=(D,W)中的缺省规则集D,是该理论的不确定因素.如果能去掉一些缺省规则而又不影响该理论的延伸,则就在一定程度上简化了该理论.本文证明了关于规范缺省理论的延伸的若干性质,利用这些性质,我们可以把某些规范缺省理论在一定条件下得以化简,有的甚至可以把它们化为一阶逻辑理论.     

Knowledge Compilation Using the Extension Rule

In this paper, we define a new class of tractable theories: EPCCL theories. Using EPCCL theories as a target language, we propose a new method for knowledge compilation. It is different from existing approaches in that both the compilation and the querying are based on the extension rule, a newly introduced inference rule. With our compilation method, arbitrary queries about the compiled knowledge base can be answered in linear time in the size of the compiled knowledge base. For some theories, the compilation can be done very efficiently, and the size of the compiled theory is small. Furthermore, our method suggests a new family of knowledge compilation methods.     

可能性缺省逻辑及其应用

本文分析了Yager用可能性理论框架来表示缺省知识的形式化方法,并测试了三类不同的应用方案,得到的结果与Reiter的缺省逻辑得到的结果相比较,表明只在具有严格的约束的缺省逻辑下,Yager的形式化方法才与Reiter的缺省逻辑具有一定的相关性,我们指出了它们在一般缺省理论下的不匹配处,并给出了以不动点机制抽改进方来消除这
些不匹配。     

Some Results on Default Logic

In the previous paper,some important properties of extensions of general default theories were given.In order to further explore default logic,a characterization of extensions is presented.And a class of defaults,so-called Auto-compatible Default Theory,is also introduced.All these essentially develop the theories of Reiter and his followers.     

Abductive Explanation-Based Learning: A Solution to the Multiple Inconsistent Explanation Problem

One problem which frequently surfaces when applying explanation-based learning (EBL) to imperfect theories is themultiple inconsistent explanation problem. The multiple inconsistent explanation problem occurs when a domain theory produces multiple explanations for a training instance, only some of which are correct. Domain theories which suffer from the multiple inconsistent explanation problem can occur in many different contexts, such as when some information is missing and must be assumed: since such assumptions can be incorrect, incorrect explanations can be constructed. This paper proposes an extension of explanation-based learning, calledabductive explanation-based learning (A-EBL) which solves the multiple inconsistent explanation problem by using set covering techniques and negative examples to choose among the possible explanations of a training example. It is shown by formal analysis that A-EBL has convergence properties that are only logarithmically worse than EBL/TS, a formalization of a certain type of knowledge-level EBL; A-EBL is also proven to be computationally efficient, assuming that the domain theory is tractable. Finally, experimental results are reported on an application of A-EBL to learning correct rules for opening bids in the game of contract bridge given examples and an imperfect domain theory.     

灰色理论在图像工程中的应用研究进展

随着传统图像信息处理技术的日趋成熟,寻求基于新理论和新思想的图像信息处理技术具有十分重要的理论意义和实用价值。为了使图像处理中的新理论——灰色理论更多地被人们所了解,首先简要介绍了灰色理论的研究内容、主要特点和基础理论;然后分别从图像处理、图像分析和图像理解3个层次来综述和分析灰色理论在图像工程中的研究进展,包括一些新的研究成果;最后,总结了在图像工程中应用灰色理论时,要解决的关键问题和未来的发展方向。研究结果显示,尽管灰色理论在图像工程中的应用研究还处于起步阶段,但其应用范围却几乎涉及了图像工程的各个方面,这充分显示它的广泛可行性、有效性,以及良好的发展潜力和应用前景。     

New system theory and its impact on control theory

Real systems can include two types of state variables – dynamic and static. While dynamic state variables are a common part of each system, static variables are not and their presence in a system may cause some problems if standard system theories are used. In this paper, it is shown that, due to a new system theory (NST), it is possible to work correctly with systems and subsystems which include not only dynamic state variables, but also static state variables. If standard system theories are used, static variables in the real system cause not only problems in describing systems but also some challenges in control theory. These challenges involve, for example, some questions of controllability, reachability, or observability of a plant that includes static variables or the optimal control design of a plant that includes statical state variables. Some of the challenges mentioned are addressed in this paper after a brief introduction of the NST.     

对称结构分析的一种新的群论方法

传统群论方法涉及特征标表、不可约表示、投影算子等高等数学理论,计算格式复杂,为此提出一种新的群论方法,该方法仅涉及群论的基本概念,无须掌握高深的数学知识,计算格式简单灵活。数值算例表明,本文方法理论可靠、计算结果正确。     

一种新的自适应谐振算法

本文提出了一个综合多种神经网络理论的学习算法ＦＴＡＲＴ（ｆｉｅｌｄｔｈｅｏｒｙ—ｂａｓｅｄａｄａｐｔｉｖｅｒｅｓｏｎａｎｃｅｔｈｅｏｒｙ），它将ＡＲＴ（ａｄａｐｔｉｖｅｒｅｓｏｎａｎｃｅｔｈｅｏｒｙ）算法、ＦｉｅｌｄＴｈｅｏｒｙ和ＡＲＴＭＡＰ等算法的优点有机结合，并以样本在实例空间出现的概率为启发信息修改分类．ＦＴＡＲＴ由于采用了不同于其它算法的冲突解决和动态扩大分类区域的方法，因此取得了较好的效果．本文还对实现ＦＴＡＲＴ算法的结果进行了验证．     

传感信号处理技术与化学传感器 发展的新趋势 关

本文从化学传感器中许多与物理量传感器不同的特点出发,论述了传感器的信号处理技术在化学传感器研制中的重要地位,重点指出了计算机技术以及几种信号处理理论的实际应用给传感器的发展带来的新趋势.     

图论的算法和应用研究

图论在学科中属于离散数学,因此它具有离散数学的许多特点。图论中许多概念和理论的产生和发展是相互独立的,因而被分成许多相互独立的专题,其算法是解决问题的一系列步骤的集合,是离散数学重要的组成部分。文章首先介绍一些图论的理论以及图的相关概念,然后对图论中经常使用到的算法作了研究和讨论,最后,并以一个具体的图论模型论述通过建立图论模型来解决实际问题了。     

“Old” theories, “New” technologies: Understanding knowledge sharing and learning in Brazilian software development companies

ContextNew technologies such as social networks, wikis, blogs and other social software enable collaborative work and are important facilitators of the learning process. They provide a simple mechanism for people to communicate and collaborate and thus support the creation of knowledge. In software-development companies they are used to creating an environment in which communication and collaboration between workers take place more effectively.ObjectiveThis paper identifies the main tools and technologies used by software-development companies in Brazil to manage knowledge and attempts to determine how these tools and technologies relate to important knowledge-sharing and learning theories and how they support the concepts described by these theories.MethodA survey was conducted in a group of Brazilian software development companies with high levels of process software maturity to see how they implement the Brazilian Software Processes Improvement model (MPS.Br) and use new tools and technologies. The survey used a qualitative analysis to identify which tools are used most and how frequently employees use them. The results of the analysis were compared with data from the literature on three knowledge-sharing and learning theories to understand how the use of these tools relates to the concepts proposed in these theories.ResultsThe results show that some of the tools used by the companies do not apply the concepts described in the theories as they do not help promote organizational learning. Furthermore, although the companies have adopted the tools, these are not often used, mainly because they are felt not to organize information efficiently.ConclusionThe use of certain tools can help promote several concepts described in the theories considered. Moreover, the use of these tools can help reduce the impact of, some common organizational problems. However, companies need to improve existing organizational policies that encourage employees to use these tools more regularly.     

计算机科学与技术中的系统论与辩证法

本文探讨了计算机科学与技术中的系统论及辩证法,包括物质和意识、联系与发展、时间和空间、理论和实践等范畴以及对立统一、质量互变、否定之否定等基本规律。应用上述理论阐述计算机软硬件系统、操作系统、程序设计语言与算法、计算机网络、计算机软硬件发展等方面存在的基本哲学问题,并将其应用于计算机教学,取得了较好的效果。     

双因素和需求理论在和谐工会建设中的探索型应用

在工会工作中,应用双因素和需求理论,即赫茨伯格的激励因素、保健因素理论和马斯洛的需求层次理论,以单位员工需求为导向,以人为本地开展工作,为全体干部员工创建一个和谐环境。本文从和谐工会的内涵和双因素、需要层次理论内容为起点,充分认识工会在构建和谐社会中的重要历史地位和作用,由浅入深地探讨了在先进理论引导下构建和谐工会的方法和思路,本研究对构建和谐工会具有很强的现实指导意义。     

T-Resolution: Refinements and Model Elimination

T-resolution is a binary rule, proposed by Policriti and Schwartz in 1995 for theorem proving in first-order theories (T-theorem proving) that can be seen – at least at the ground level – as a variant of Stickel's theory resolution. In this paper we consider refinements of this rule as well as the model elimination variant of it. After a general discussion concerning our viewpoint on theorem proving in first-order theories and a brief comparison with theory resolution, the power and generality of T-resolution are emphasized by introducing suitable linear and ordered refinements, uniformly and in strict analogy with the standard resolution approach. Then a model elimination variant of T-resolution is introduced and proved to be sound and complete; some experimental results are also reported. In the last part of the paper we present two applications of T-resolution: to constraint logic programming and to modal logic.     

Ethical theory, codes of ethics and IS practice

Ethical issues, with respect to computer-based information systems, are important to the individual IS practitioner. These same issues also have an important impact on the moral well-being of organizations and societies. Considerable discussion has taken place in the Information Systems (IS) literature on specific ethical issues, but there is little published work which relates these issues to mainstream ethical theory. This paper describes a range of ethical theories drawn from philosophy literature and uses these theories to critique aspects of the newly revised ACM Code of Ethics. Some in the IS field on problematic ethical issues which are not resolved by the Code are then identified and discussed. The paper draws some implications and conclusions on the value of ethical theory and codes of practice, and on further work to develop existing ethical themes and to promote new initiatives in the ethical domain.     

FOUNDATIONS OF O-THEORY: MEASUREMENTS AND RELATION TO FUZZY SET THEORY

A measurement framework for O-theory, an algebra of random sets, is presented. The framework is probabilistic and derived from experimental measurements of evidential support. It is used to quantify the probabilistic masses needed in O-theory. This framework allows a connection to be made between this random set algebra and the possibilistic form of fuzzy set theory. Instances in which these two different representations of the same experimental data are equivalent are explored. The relationship between some basic operators in both theories are then discussed, along with their connection to Dempster-Shafer theory. Finally, several illustrative examples of deductive inferencing under uncertainty are solved. The equivalence of the representations of the results in both uncertainty theories is demonstrated.