238,072 research outputs found

    Applications of Expert Systems in Transport

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    BACKGROUND Experienced judgement and specialist knowledge are essential to the proper specification, understanding and interpretation of data and computer analyses. The human expert has traditionally supplied this knowledge and judgement with the computer doing the necessary number-crunching. However, artificial intelligence (AI) research provides ways of embodying this knowledge and judgement within computer programs. Despite an early lead in the field, UK research and developmnent into AI techniques was held back in the 1970s when the then Science Research Council took the view that the 'combinatorial explosion' of possibilities would be an insurmountable obstacle to AI developent. But in America and Japan research continued, and the surge of interest in the 1980s has been a consequence of the 'Fifth Generation Computer' research programme initiated by Japan (Feigenbaum and McCorduck; 1984). This led in Europe to the ESPRIT programme of advanced technology research, and in the UK to the Alvey programme (Department of Industry, 1982). As a result, all sectors of industry have been encouraged to consider how such advanced technology can be applied, and the transport industry is no exception. This paper sets out to explain some of the relevant techniques in simple terms, and to describe a number of situations in which transport planning and operations might be helped through their use, illustrating this by reference to the pioneering work going on in transport applications in the USA, Britain and Australia

    The development of a prototype intelligent user interface subsystem for NASA's scientific database systems

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    The National Space Science Data Center (NSSDC) has initiated an Intelligent Data Management (IDM) research effort which has as one of its components the development of an Intelligent User Interface (IUI).The intent of the latter is to develop a friendly and intelligent user interface service that is based on expert systems and natural language processing technologies. The purpose is to support the large number of potential scientific and engineering users presently having need of space and land related research and technical data but who have little or no experience in query languages or understanding of the information content or architecture of the databases involved. This technical memorandum presents prototype Intelligent User Interface Subsystem (IUIS) using the Crustal Dynamics Project Database as a test bed for the implementation of the CRUDDES (Crustal Dynamics Expert System). The knowledge base has more than 200 rules and represents a single application view and the architectural view. Operational performance using CRUDDES has allowed nondatabase users to obtain useful information from the database previously accessible only to an expert database user or the database designer

    ART-Ada: An Ada-based expert system tool

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    The Department of Defense mandate to standardize on Ada as the language for software systems development has resulted in increased interest in making expert systems technology readily available in Ada environments. NASA's Space Station Freedom is an example of the large Ada software development projects that will require expert systems in the 1990's. Another large scale application that can benefit from Ada based expert system tool technology is the Pilot's Associate (PA) expert system project for military combat aircraft. Automated Reasoning Tool (ART) Ada, an Ada Expert system tool is described. ART-Ada allow applications of a C-based expert system tool called ART-IM to be deployed in various Ada environments. ART-Ada is being used to implement several prototype expert systems for NASA's Space Station Freedom Program and the U.S. Air Force

    TROUBLE 3: A fault diagnostic expert system for Space Station Freedom's power system

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    Designing Space Station Freedom has given NASA many opportunities to develop expert systems that automate onboard operations of space based systems. One such development, TROUBLE 3, an expert system that was designed to automate the fault diagnostics of Space Station Freedom's electric power system is described. TROUBLE 3's design is complicated by the fact that Space Station Freedom's power system is evolving and changing. TROUBLE 3 has to be made flexible enough to handle changes with minimal changes to the program. Three types of expert systems were studied: rule-based, set-covering, and model-based. A set-covering approach was selected for TROUBLE 3 because if offered the needed flexibility that was missing from the other approaches. With this flexibility, TROUBLE 3 is not limited to Space Station Freedom applications, it can easily be adapted to handle any diagnostic system

    ART-Ada design project, phase 2

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    Interest in deploying expert systems in Ada has increased. An Ada based expert system tool is described called ART-Ada, which was built to support research into the language and methodological issues of expert systems in Ada. ART-Ada allows applications of an existing expert system tool called ART-IM (Automated Reasoning Tool for Information Management) to be deployed in various Ada environments. ART-IM, a C-based expert system tool, is used to generate Ada source code which is compiled and linked with an Ada based inference engine to produce an Ada executable image. ART-Ada is being used to implement several expert systems for NASA's Space Station Freedom Program and the U.S. Air Force

    Cooperation between expert knowledge and data mining discovered knowledge: Lessons learned

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    Expert systems are built from knowledge traditionally elicited from the human expert. It is precisely knowledge elicitation from the expert that is the bottleneck in expert system construction. On the other hand, a data mining system, which automatically extracts knowledge, needs expert guidance on the successive decisions to be made in each of the system phases. In this context, expert knowledge and data mining discovered knowledge can cooperate, maximizing their individual capabilities: data mining discovered knowledge can be used as a complementary source of knowledge for the expert system, whereas expert knowledge can be used to guide the data mining process. This article summarizes different examples of systems where there is cooperation between expert knowledge and data mining discovered knowledge and reports our experience of such cooperation gathered from a medical diagnosis project called Intelligent Interpretation of Isokinetics Data, which we developed. From that experience, a series of lessons were learned throughout project development. Some of these lessons are generally applicable and others pertain exclusively to certain project types
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