24 August 1998 Generation of multimodels and selection of the optimal model for real-time simulation
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Proceedings Volume 3369, Enabling Technology for Simulation Science II; (1998); doi: 10.1117/12.319331
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States
Abstract
As we model a complex system, modelers need a way to better handle multiple perspectives of the system. Finding a model of a complex system that is at the right level of detail for a specific purpose is a difficult task. Also there is a need to simulate the model under a time constraint, when the modeled system has to meet a given deadline in order to avoid hard/soft disasters. Considering these different needs, our question is 'How to determine the optimal model that simulates the system by a given deadline while still producing good quality at the right level of detail.' We try to answer this question on multimodeling object oriented simulation environment (MOOSE). The proposed framework has three phase: (1) Generation of multimodels in MOOSE using both structural and behavioral abstraction technique, (2) Assessment of quality and runtime for each generated model, (3) Selection of the optimal model for a given real-time constraint. A more detailed model is selected when we have enough time to simulate but a less detailed model is selected when the deadline is immediate.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kangsun Lee, Paul A. Fishwick, "Generation of multimodels and selection of the optimal model for real-time simulation", Proc. SPIE 3369, Enabling Technology for Simulation Science II, (24 August 1998); doi: 10.1117/12.319331; https://doi.org/10.1117/12.319331
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KEYWORDS
Computer simulations

Systems modeling

Neural networks

Complex systems

Process modeling

Computing systems

Instrument modeling

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