Dynamic system evolutionary modeling: the case of SARS in beijing

  • Authors:

  • Chenzhong Yang;Zhuo Kang;Yan Li

  • Affiliations:

  • School of Mathematics and Computer Science, Guizhou University for Nationalities, Guiyang, Guizhou, China;Computation Center, Wuhan University, Wuhan, Hubei, China;Computation Center, Wuhan University, Wuhan, Hubei, China

  • Venue:
  • ISICA'07 Proceedings of the 2nd international conference on Advances in computation and intelligence
  • Year:
  • 2007

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Abstract

In this paper a new evolutionary algorithm for automatically modeling of dynamic systems is proposed. The algorithm is based on a scalable multigene chromosome representation with fixed length, which is similar in form to gene expression programming (GEP) proposed by Ferreira. The complexity of the automatic programming of modeling is determined by length of chromosome, and the complexity of function set and terminal set used for modeling. For modeling dynamic systems, the systems of ordinary differential equations are used. The new algorithm is used to model the super-spreading events of severe acute respiratory syndrome (SARS) in Beijing, because Beijing experienced the largest outbreak of SARS, with 2500 cases reported between March and June, 2003. Two types of ODE models, systems of ordinary differential equations and higher order ordinary differential equations are automatically discovered by the new methodology from the reported data (http://www.Beijing.gov.cn/resource/ Detail.asp?Resource ID=66070).