Knowledge-based decision support for space station assembley sequence planning
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Knowledge-based decision support for space station assembley sequence planning final report.

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Published by ISX Corporation, National Technical Information Service, distributor in Westlake Village, CA, [Springfield, Va .
Written in English

Subjects:

  • Space stations.

Book details:

Edition Notes

Other titlesKnowledge based decision support for space ....
SeriesNASA contractor report -- NASA CR-193048.
ContributionsUnited States. National Aeronautics and Space Administration.
The Physical Object
FormatMicroform
Pagination1 v.
ID Numbers
Open LibraryOL18060121M

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Knowledge-based systems are potentially powerful tools for improving the results of automated or interactive design procedures. Expert Space Planner is a prototype of such a system that uses.   This paper presents a novel approach and system for the automatic generation, selection and evaluation, optimisation, and simulation of assembly plans. The information and knowledge about a product and its assembly (e.g. assembly constraints, solid model and CAD database, heuristic rules) are described using a hybrid approach and model with numeric and Cited by:   In this study, we developed a knowledge-based engineering (KBE) system to assist engineers in promptly predicting a near-optimal assembly sequence. A three-stage assembly optimization approach with some heuristic working rules was employed to establish the proposed system. In the first stage, Above Graph and a transforming rule were used to create Cited by: Knowledge -Based Project Planning Héctor Muñoz -Avila 1,2 Kalyan Gupta 2,3 David W. Aha 3 Dana S. Nau 1 1 Department of Computer Science, University of Maryland, College Park, MD 2Navy Center for Applied Research in Artificial Intelligence, Naval Research Laboratory, Washington, DC 3ITT Industries AES Division, Alexandria, VA

Knowledge-Based IMRT Planning AAPM Knowledge Models Decision Support Models DUKE University Radiation Oncology Thank You & Happy Planning With All Types of Knowledge Formats AAPM Title: Microsoft PowerPoint - Created Date. Model base. Mathematical models are good for application to well-structured decision problems that led to optimization solutions, while rule-based knowledge systems are good at dealing with unstructured and semi-structured problems where heuristic algorithms are used to obtain feasible solutions (Tian, Ma, & Liu, ).This study uses a model base on the decision Cited by: Reference as: Onions, P.E.W. (), "A methodology for knowledge based project management", working and unpublishedFile Size: 75KB. The architecture of the knowledge-based intelligent decision support system for National Defense Budget Planning The KIDSS system is composed of four main components, as shown in Fig. 3: the database management subsystem, the model base subsystem, the knowledge acquisition subsystem, and the dialogue by:

Making Space and Place for Knowledge Production: Socio-Spatial Development of Knowledge Community Precincts: /ch In the knowledge era the importance of making space and place for knowledge production is clearly understood worldwide by many city administrations that areCited by: 3. Book Review D.B. Lenat and R.V. Guha, Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project * John F. Sowa IBM Systems Research, Columbus Avenue, Thornwood, NY , USA Revised February The Cyc project, started by Doug Lenat at MCC in , is the most. Project scheduling systems are essential tools for helping inexperienced project managers plan and monitor projects and for helping experienced project professionals analyze and evaluate project progress. This article explains the development of a knowledge-based schedule planning system. In doing so, it first explores the literature on the need for more effective construction . Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project [Lenat, Douglas B., Guha, R. V.] on *FREE* shipping on qualifying offers. Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project5/5(3).