کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1135663 | 956107 | 2008 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Neural network-based simulation metamodels for predicting probability distributions Neural network-based simulation metamodels for predicting probability distributions](/preview/png/1135663.png)
Simulation is an important tool for supporting decision-making under uncertainty, particularly when the system under consideration is too complex to evaluate analytically. The amount of time required to generate large numbers of simulation replications can be prohibitive, however, necessitating the use of a simulation metamodel in order to describe the behavior of the system under new conditions. The purpose of this study is to examine the use of neural network metamodels for representing output distributions from a stochastic simulation model. A series of tests on a well-known simulation problem demonstrate the ability of the neural networks to capture the behavior of the underlying systems and to represent the inherent uncertainty with a reasonable degree of accuracy.
Journal: Computers & Industrial Engineering - Volume 54, Issue 4, May 2008, Pages 879–888