Document Type
Thesis
Degree
Master of Science (MS)
Major/Program
Please see currently inactive department below.
Major/Program
Industrial and Systems Engineering
First Advisor's Name
Martha A. Centeno
First Advisor's Committee Title
Committee Chair
Second Advisor's Name
Armando Barreto
Third Advisor's Name
Kia Makki
Date of Defense
3-29-2004
Abstract
An integration framework for Neural Networks (NN) and Goal Driven Simulation (GDS) has been designed. It offers no constraints regarding number of variables (n>3) and it does not have domain restrictions. The effectiveness of the framework was tested by observing the computational time required for obtaining responses and for training, and by assessing its accuracy for different scenarios. This framework has achieved the automation objective set by GDS under a shorter time frame, as it reduces the time from more than 42 hours to less than 14. A trained NN generates responses to queries almost instantaneously. However, it requires time re-building and re-training new NNs when changes are made to the system represented by the model. If these changes are rare, the payoff is worthy as this approach gives users more flexibility.
Identifier
FI14060853
Recommended Citation
Clavijo, Maria F., "Using neural networks for goal driven simulation" (2004). FIU Electronic Theses and Dissertations. 2383.
https://digitalcommons.fiu.edu/etd/2383
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Comments
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