Discrete Event simulation is a natural way to simulate models that are characterized by heterogeneity in their spatio-temporal behavior. This paper describes a valley fever spore-propagation model that describes the t...
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Discrete Event simulation is a natural way to simulate models that are characterized by heterogeneity in their spatio-temporal behavior. This paper describes a valley fever spore-propagation model that describes the time dependent spatial distribution of spores in southern Arizona. Two implementations of this model are examined and their execution times are compared. A discrete event model exploits the fact that only a few areas are favorable for the growth of the fungus at any given time. This allows it to schedule events only at the areas that are favorable. In contrast, the existing discrete time model cannot take advantage of the few areas that are favorable.
The success of DEVS methods for simulating large continuous models calls for more in-depth examination of the applicability of discrete events in modeling continuous phenomena. We present a concept of event set and an...
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Diverse modeling and simulation methods are being applied in the area of Systems Biology. Most models in Systems Biology can easily be located within the space that is spanned by three dimensions of modeling: continuo...
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This paper presents the results of applying an incremental simulation-based design process to study a robotic convoy system. Robot-in-the-loop simulation, as a major step in this process, allows the system to be measu...
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This paper presents a numerical study of the flow and segregation of particles over flat blades in a vertical cylindrical mixer by using discrete element method. simulations are conducted on binary mixtures of spheres...
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Rational least-squares techniques are commonly used to build compact macromodels of passive microwave components. This paper describes a technique which calculates rational least-squares fitting models by matching S-p...
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Rational least-squares techniques are commonly used to build compact macromodels of passive microwave components. This paper describes a technique which calculates rational least-squares fitting models by matching S-parameter frequency data-samples and higher-order frequency derivatives (or moments) using orthonormal polynomial basis functions to improve the numerical accuracy. Some considerations are given about the optimal choice ofpolynomial basisfunctions.
Crowds of non-combatants play a large and increasingly recognized role in modern military operations, and often create substantial difficulties for the combatant forces involved. However, in spite of their potential s...
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This paper deals with modeling and simulation of surface forest fire spread and suppression using the discrete event system specification (DEVS) cellspace approach. The event-based modeling approach allows for timely ...
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This paper deals with modeling and simulation of surface forest fire spread and suppression using the discrete event system specification (DEVS) cellspace approach. The event-based modeling approach allows for timely simulation-based predictions of forest, fire spread and suppression in uniform and non-uniform environmental conditions. This paper proposes a conceptual model for a coupled forest cell model comprising of a forest cell agent atomic model and a forest cell atomic model The forest cell agent atomic model will allow for modeling and simulation of more complex fire suppression strategies to control fire spread. The proposed basic model provides an advance toward developing a real-time or fast-as-can decision support simulation system for predicting forest fire spread and the effects of fire suppression attempts.
In today's interconnected networks, Intrusion Detection Systems (IDSs), encryption devices, firewalls and other hardware and software solutions are critical in providing complete security solutions for corporation...
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simulation composability has been much more difficult to realize than some initially imagined. We believe that success lies in explicit considerations for the adaptability of components. In this paper, we show that th...
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ISBN:
(纸本)9780780395190
simulation composability has been much more difficult to realize than some initially imagined. We believe that success lies in explicit considerations for the adaptability of components. In this paper, we show that the complexity of optimal component selection for adaptable components is NP-complete. However, our approach allows for the efficient adaptation of components to construct a complex simulation in the most flexible manner while allowing the greatest opportunity to meet all requirements, all the while reducing time and costs. We demonstrate that complexity can vary from polynomial, to NP, and even to exponential as a function of seemingly simple decisions made about the nature of dependencies among components. We generalize these results to show that regardless of the types or reasons for dependencies in component selection, just their mere existence makes this problem very difficult to solve optimally.
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