화학공학소재연구정보센터
홈 로그인 로그아웃 연락처 사이트맵
Korean Journal of Chemical Engineering, Vol.18, No.5, 623-629, September, 2001
DOI10.1007/BF02706377  Export Citation
A Method of Model Validation for Chaotic Chemical Reaction Systems Based on Neural Network
Hwi Jin Kim, and Kun Soo Chang†
  • Department of Chemical Engineering and Automation Research Center, Pohang University of Science and Technology, San 31 Hyoja Dong, Pohang 790-784, Korea
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A chaotic system with measurable state variables fewer than the degrees of freedom of the system is identified with the Artificial Neural Network (ANN) method combined with dynamic training. Instead of using the usual method of Sum of Square Errors (SSE), the identified models are validated with the return maps (embedded trajectories), the largest Lyapunov exponent, and the correlation dimension when there is no exogenous input, and bifurcation diagram when there is an exogenous input. This method is demonstrated for nonisothermal, irreversible, first-order, series reaction A -> B -> C in a CSTR.
Keywords:Chaos;Neural Network;Dynamic Training;System Identification;Model Validation
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