Applications of artificial neural networks in chemical engineering

A growing literature within the field of chemical engineering describing th e use of artificial neural networks (ANN) has evolved for a diverse range o f engineering applications such as fault detection, signal processing, proc ess modeling, and control. Because ANN are nets of basis functions, they ca n provide good empirical models of complex nonlinear processes useful for a wide variety of purposes. This article describes certain types of neural n etworks that have proved to be effective in practical applications, mention s the advantages and disadvantages of using them, and presents four detaile d chemical engineering applications. In the competitive field of modeling, ANN have secured a niche that now, after one decade, seems secure.