Emergent system identification using particle swarm optimization

Mark S. Voss; Xin Feng

doi:10.1117/12.446767

23 October 2001 Emergent system identification using particle swarm optimization

Mark S. Voss, Xin Feng

Proceedings Volume 4512, Complex Adaptive Structures; (2001) https://doi.org/10.1117/12.446767
Event: Complex Adaptive Structures, 2001, Hutchinson Island, FL, United States

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.

Citation Download Citation

Mark S. Voss and Xin Feng "Emergent system identification using particle swarm optimization", Proc. SPIE 4512, Complex Adaptive Structures, (23 October 2001); https://doi.org/10.1117/12.446767

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