Dynamic refinement of a campaign simulation

被引：0

作者：

Fall, TC ^{[1
]}

机构：

[1] Lockheed Martin Management & Data Syst, Sunnyvale, CA 94089 USA

来源：

ENABLING TECHNOLOGY FOR SIMULATION SCIENCE III | 1999年 / 3696卷

关键词：

simulation; aggregation; clustering; Monte Carlo; air campaign simulation;

D O I：

10.1117/12.351193

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In a project sponsored by AFRL/IFSB, the Dynamic Focusing Architecture (DFA) tool is being use to guide when and where more fidelity in a campaign model would be valuable. DFA predicts ranges of outcomes; for those of most consequence, it traces back to which components were mast responsible. Those components become candidates for finer level simulation. There is some commonality of intent between this and SimPath, being done by Gong, Ho and Gilmer, which does trajectory management by clustering trajectories in discrete event simulations. The DFA approach clusters outcomes from time stepped simulations, but the goals are similar. This paper will discuss the two approaches as well as the current status of this effort.

引用

页码：88 / 95

页数：8