화학공학소재연구정보센터
홈 로그인 로그아웃 연락처 사이트맵
Korean Journal of Chemical Engineering, Vol.17, No.4, 373-392, July, 2000
DOI10.1007/BF02706848  Export Citation
Applications of Artificial Neural Networks in Chemical Engineering
David M. Himmelblau†
  • Department of Chemical Engineering, The University of Texas Austin, Texas 78731, USA
E-mail:
A growing literature within the field of chemical engineering describing the use of artificial neural networks (ANN) has evolved for a diverse range of engineering applications such as fault detection signal processing, process modeling, and control. Because ANN are nets of basis functions, they can provide good empirical models of complex nonlinear processes useful for a wide variety of purposes. This article describes certain types of neural networks that have proved to be effective in practical applications, mentions the advantages and disadvantage of using them, and presents four detailed chemical engineering applications. In the competitive field of modeling, ANN have secured a niche that now, after one decade, seems secure.
Keywords:Artificial Neural Networks;Control;Data Rectification;Fault Detection;Modeling
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