Title :
On the application of genetic programming to chemical process systems
Author :
McKay, Ben ; Willis, Mark J. ; Barton, Geoffrey W.
Author_Institution :
Dept. of Chem. Eng., Sydney Univ., NSW, Australia
fDate :
29 Nov-1 Dec 1995
Abstract :
A genetic programming approach is utilised to develop mathematical models of chemical process systems. Having discussed genetic programming in general, two examples are used to reveal the utility of the technique. It is shown how the method can discriminate between relevant and irrelevant process inputs, evolving to yield parsimonious model structures that accurately represent process characteristics. This removes the need for restrictive assumptions about the form of the data and the structure of the required model. In addition, as the technique determines complex nonlinear relationships in the data, non-intuitive process features are revealed with comparative ease
Keywords :
chemical engineering computing; chemical industry; genetic algorithms; chemical process systems; complex nonlinear relationships; genetic programming; irrelevant process inputs; mathematical models; nonintuitive process features; parsimonious model structures; relevant process inputs; Artificial neural networks; Australia; Chemical processes; Costs; Data engineering; Genetic programming; Information retrieval; Mathematical model; Memory; Performance analysis;
Conference_Titel :
Evolutionary Computation, 1995., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2759-4
DOI :
10.1109/ICEC.1995.487470
