Rule-based generation of model structures in multifaceted modeling and system design

Jerzy W Rozenblit, Yueh M. Huang

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

A framework for aiding the construction of simulation models in system design problems is presented. The framework employs concepts of artificial intelligence and simulation modeling. A knowledge representation scheme called system entity structure expresses information about the structure of the system to be designed and its corresponding models. More specifically, the entity structure represents objects and their attributes, decompositions, and taxonomies. A knowledge base of production rules is defined for a given design domain and is incorporated in an expert system shell which recommends a feasible configuration of design objects from the system entity structure, based on specific design objectives, constraints, and requirements. This configuration is a basis for constructing a model of the system. The methodology for constructing the system entity structure and its corresponding rule base is presented. A case study based on a high level robot design problem is discussed to illustrate the conceptual framework.

Original languageEnglish (US)
Pages (from-to)330-344
Number of pages15
JournalORSA journal on computing
Volume3
Issue number4
StatePublished - Sep 1991

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Model structures
Systems analysis
Knowledge representation
Taxonomies
Expert systems
Artificial intelligence
Robots
Decomposition
Modeling
Rule-based
System design
Computer simulation

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Rule-based generation of model structures in multifaceted modeling and system design. / Rozenblit, Jerzy W; Huang, Yueh M.

In: ORSA journal on computing, Vol. 3, No. 4, 09.1991, p. 330-344.

Research output: Contribution to journalArticle

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