Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Sign In to gain access to subscriptions and/or personal tools.
SIMULATION
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Haddock, J.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

Other

An expert system framework based on a simulation generator

Jorge Haddock

Center for Industrial and Management Engineering Rensselaer Polytechnic Institute Troy, New York 12180-3590

Expert Systems (ES) implementations automatically perform tasks for which specially trained or talented people have been re quired. Fifth generation simulation systems integrate the tools developed in the fourth generation and capture the knowledge of the expert programmer as well as that of the simulation model ing expert. Haddock has programmed a user- oriented simula tion generator for the design and control of flexible manufac turing systems (FMS). The development of an ES based on the generator is described in this paper.

The system to be described solely requires knowledge of the system to be simulated from the user. FORTRAN written sub routines, incorporated within the software structure of SIMAN, interpret the results of experimental runs and make statistical inferences about the performance measure.

Simulation generators can assist simulationists in model develop ment and update, as well as in the analysis of alternative sce narios. A very desirable feature of Intelligent Front Ends (IFEs) is to have the capabilities of analyzing their output. These capa bilities not only reduce the total time required to perform the simulation, but also prevent its misuse.

Key Words: program generators • simulators • validation

SIMULATION, Vol. 48, No. 2, 45-53 (1987)
DOI: 10.1177/003754978704800202
Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?


This article has been cited by other articles:


Home page
 SIMULATIONHome page
Kun Chang Lee, Won Jun Lee, O Byung Kwon, Jae Ho Han, and Pyung Il Yu
Strategic Planning Simulation Based on Fuzzy Cognitive Map Knowledge and Dif ferential Game
SIMULATION, November 1, 1998; 71(5): 316 - 327.
[Abstract] [PDF]

Home page
 SIMULATIONHome page
G. T. Mackulak, J. K. Cochran, and P. A. Savory
Ascertaining Important Features For Industrial Simulation Environments
SIMULATION, October 1, 1994; 63(4): 211 - 221.
[Abstract] [PDF]

Home page
 SIMULATIONHome page
G. V. Merkuryeva and Y. A. Merkuryev
Knowledge Based Simulation Systems - A Review
SIMULATION, February 1, 1994; 62(2): 74 - 89.
[Abstract] [PDF]

Home page
 SIMULATIONHome page
J. M. Mellichamp and Y. H. Park
A statistical expert system for simulation analysis
SIMULATION, April 1, 1989; 52(4): 134 - 139.
[Abstract] [PDF]

Home page
 SIMULATIONHome page
M. C. Stairmand and W. Kreutzer
POSE: a Process-Oriented Simulation Environment embedded in SCHEME
SIMULATION, April 1, 1988; 50(4): 143 - 153.
[Abstract] [PDF]

Home page
 SIMULATIONHome page
K. J. Murray and S. V. Sheppard
Knowledge-based simulation model specification
SIMULATION, March 1, 1988; 50(3): 112 - 119.
[Abstract] [PDF]