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Proceedings Paper

Emergent system identification using particle swarm optimization
Author(s): Mark S. Voss; Xin Feng
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Paper Abstract

Complex Adaptive Structures can be viewed as a combination of Complex Adaptive Systems and fully integrated autonomous Smart Structures. Traditionally when designing a structure, one combines rules of thumb with theoretical results to develop an acceptable solution. This methodology will have to be extended for Complex Adaptive Structures, since they, by definition, will participate in their own design. In this paper we introduce a new methodology for Emergent System Identification that is concerned with combining the methodologies of self-organizing functional networks (GMDH - Alexy G. Ivakhnenko), Particle Swarm Optimization (PSO - James Kennedy and Russell C. Eberhart) and Genetic Programming (GP - John Koza). This paper will concentrate on the utilization of Particle Swarm Optimization in this effort and discuss how Particle Swarm Optimization relates to our ultimate goal of emergent self-organizing functional networks that can be used to identify overlapping internal structural models. The ability for Complex Adaptive Structures to identify emerging internal models will be a key component for their success.

Paper Details

Date Published: 23 October 2001
PDF: 10 pages
Proc. SPIE 4512, Complex Adaptive Structures, (23 October 2001); doi: 10.1117/12.446767
Show Author Affiliations
Mark S. Voss, Marquette Univ. (United States)
Xin Feng, Marquette Univ. (United States)

Published in SPIE Proceedings Vol. 4512:
Complex Adaptive Structures
William B. Spillman Jr., Editor(s)

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