fishwick@fish.cis.ufl.edu (Paul Fishwick) (08/14/89)
For a pre-print of this article, please send a note with your address to:
paulette@bikini.cis.ufl.edu
NEURAL NETWORK MODELS IN SIMULATION:
A COMPARISON WITH TRADITIONAL MODELING APPROACHES
Paul A. Fishwick
Department of Computer and Information Science
University of Florida
Bldg. CSE, Room 301
Gainesville, FL 32611
INTERNET: fishwick@fish.cis.ufl.edu
To be presented at:
The Winter Simulation Conference, Dec. 1989
ABSTRACT
Neural models are enjoying a resurgence in systems research primarily
due to a general interest in the connectionist approach to
modeling in artificial intelligence and to the availability of faster
and cheaper hardware on which neural net simulations can be executed.
We have experimented with using a multi-layer neural network model
as a simulation model for a basic ballistics model. In an effort to
evaluate the efficiency of the neural net implementation for simulation
modeling, we have compared its performance with traditional methods
for geometric data fitting such as linear
regression and surface response methods. Both of the latter approaches
are standard features in many statistical software packages. We have
found that the neural net model appears to be inadequate in most respects
and we hypothesize that accuracy problems arise, primarily, because
the neural network model does not capture the system structure
characteristic of all physical models. We discuss the experimental
procedure, issues and problems, and finally consider
possible future research directions.
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| Prof. Paul A. Fishwick.... INTERNET: fishwick@bikini.cis.ufl.edu |
| Dept. of Computer Science. UUCP: gatech!uflorida!fishwick |
| Univ. of Florida.......... PHONE: (904)-335-8036 |
| Bldg. CSE, Room 301....... FAX is available |
| Gainesville, FL 32611..... |
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