摘要:

In the past decade, the use of control and diagnostic reasoning systems in different areas of government, industry, and university operations has increased. A great number of these systems find their basis in engineering, specifically in process control. The majority of the time devoted to the development of these systems is spent in the areas of Knowledge Engineering (KE) and Knowledge Acquisition (KA). Extensive research for the development of systems that perform the KE task is under way. This article presents an approach toward automatic knowledge acquisition. The objective of this research was to construct a complete knowledge base for a diagnostic and control reasoning system from information that resides in Computer Aided Design (CAD) databases. This work will decrease the amount of time spent in the manual generation of knowledge bases for diagnostic reasoning systems, ft will also enable the creation of more reliable knowledge bases since less hand coding is required.

ISSN:0883-9514    

DOI:10.1080/08839519308949979

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

摘要:

An innovative framework is presented that responds to the needs of a user that may want to have punctual personalized information integrated with the possibility of accessing standard browsable information through the same generated text. An implemented system is illustrated for generating natural language texts immersed in a hypermedia network. The architecture of the system and the specific solution given to the various components and their integration are described: the strategic component and its relation to the knowledge representation and to the user model, the tactical component and its connection to the strategic one, and the hypertext manager that accomodates the new linked text. Throughout the article explicit reference is made to the implementation solutions adopted and to examples relative to the experimentation of the work as part of the ALFRESCO interactive system.

ISSN:0883-9514    

DOI:10.1080/08839519308949980

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

摘要:

This article presents a method for detecting device failures using scale-driven object matching and discusses the use of this method to facilitate object-oriented device diagnosis. A device-independent class called scale, introduced to hide the method from the objects, provides abstraction mechanisms that facilitate knowledge acquisition and system integration. Using this class, plans for diagnosis can be generated from the mismatches resulting from comparing prototypical devices with faulty devices.

ISSN:0883-9514    

DOI:10.1080/08839519308949981

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

摘要:

This article investigates the integration of computer-aided design, manufacturing, and testing for gears using a distributed intelligence system. The integration architecture, principles, and implementation for computer integrated manufacturing systems (CIMS) are presented. An integrated intelligent system is developed, which has a parallel hierarchical structure in general and a meta-system as its kernel to manage and control the selection, communication, coordination, and operation of the subsystem. The functions and configuration of the meta-system are discussed in detail. A gear integrated manufacturing system (GIMS) is implemented to demonstrate the feasibility and capability of the integrated intelligent system.

ISSN:0883-9514    

DOI:10.1080/08839519308949982

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

摘要:

As is well known, the Dempster-Shafer mathematical theory of evidence, which employs the use of belief functions, has been used to perform uncertain inference in expert systems and artificial intelligence. As is also well known, many fault this discipline for two reasons: (1) Dempster-Shafer theory is not probability theory, and there exist cogent arguments for using only probability theory to perform uncertain inference; (2) As shown by a number of authors, mechanical applications of belief functions can lead to quite unacceptable results. In a 1990 special issue of the International Journal of Approximate Reasoning, which was devoted to a discussion of belief functions, these criticisms were forwarded and various interpretations of belief functions were offered. In his response to the discussion in the special issue, Shafer showed the problems with these criticisms and interpretations, and he once again explained how he meant for belief functions to be interpreted. In this article, this defense is furthered in two ways: (1) It is shown that belief functions, as Shafer intends them to be interpreted, use probability theory in the same way as the traditional statistical tool, significance testing; and (2) A problem is given for which an application of belief functions yields a meaningful solution while a Bayesian analysis does not.

ISSN:0883-9514    

DOI:10.1080/08839519308949983

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor