A comparative analysis of regression and neural networks in simulation metamodeling
Abstract
In today's business, a company must be able to make efficient use of its available resources. Decision making techniques play a significant role in enabling companies to optimize their limited resources. Discrete-Event Computer Simulation is one of the more widely used decision making tools. However, simulation in itself is a descriptive tool, and provides solutions to different alternatives that an analyst wishes to explore. Because running a simulation is computationally expensive, randomly trying different alternatives results in inefficient practice at a high cost. Simulation Metamodeling is an inexpensive method of exploring various alternatives that can be used with simulation models as decision-making tools. Simulation metamodels reduce the time needed to explore and optimize a simulated scenario. However the appropriate simulation metamodel to be used for a specific goal has not yet be identified. This thesis will investigate the construction of two types of metamodels for a given simulated scenario (regression metamodels and neural network metamodels), and compare their ability to accurately predict the simulation model. Conclusions will be drawn on the ability of each to accurately predict the simulation model, and suggestions will be made on the type of characteristics to which each method is suited.
Notes
This item is only available in print in the UCF Libraries. If this is your thesis or dissertation, you can help us make it available online for use by researchers around the world by STARS for more information.
Thesis Completion
2000
Semester
Spring
Advisor
Mollaghasemi, Mansooreh
Degree
Bachelor of Science (B.S.)
College
College of Engineering
Degree Program
Industrial Engineering
Subjects
Dissertations, Academic -- Engineering;Engineering -- Dissertations, Academic;Computer simulation;Decision making -- Computer simulation;Neural networks (Computer science)
Format
Identifier
DP0021624
Language
English
Access Status
Open Access
Length of Campus-only Access
None
Document Type
Honors in the Major Thesis
Recommended Citation
St. Matthew Daniel, Eyitope, "A comparative analysis of regression and neural networks in simulation metamodeling" (2000). HIM 1990-2015. 198.
https://stars.library.ucf.edu/honorstheses1990-2015/198