Survivability of complex system - Support vector machine based approach

Y. Hong, N. Gautam, S. R.T. Kumara, A. Surana, H. Gupta, S. Lee, V. Narayanan, H. Thadakamalla, M. Brinn, M. Greaves

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations

Abstract

Logistic systems which are inherently distributed, in general can be classified as complex systems. Survivability of these systems under varying environment conditions is of paramount importance. Different environmental conditions in which the logistic system resides are translated into several stresses. These in turn will manifest as internal stresses. Logistic systems can be modeled as a collection of software agents. Each agent's behavior is a result of the stresses imposed. Predicting the agents' collective behavior is of paramount importance to ensure survivability. Analytical modeling of such systems becomes very difficult, albeit impossible. In this paper, we study a supply chain in which a real life scenario is used. We implement the supply chain in Cougaar (Cognitive Agent Architecture developed by DARPA) and develop a predictor, based on Support Vector Machine. We report our methodology and results with real-life experiments and stress scenarios.

Original languageEnglish (US)
Pages153-158
Number of pages6
StatePublished - 2002
Externally publishedYes
EventProceedings of the Artificial Neutral Networks in Engineering Conference:Smart Engineering System Design - St. Louis, MO, United States
Duration: Nov 10 2002Nov 13 2002

Conference

ConferenceProceedings of the Artificial Neutral Networks in Engineering Conference:Smart Engineering System Design
Country/TerritoryUnited States
CitySt. Louis, MO
Period11/10/0211/13/02

ASJC Scopus subject areas

  • Software

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