Systems modelling using genetic programming

被引：0
|
作者：
Willis, M [1 ]
Hiden, H [1 ]
Hinchliffe, M [1 ]
McKay, B [1 ]
Barton, GW [1 ]
机构：
[1] UNIV SYDNEY, DEPT CHEM ENGN, SYDNEY, NSW 2006, AUSTRALIA
来源：
COMPUTERS & CHEMICAL ENGINEERING | 1997年 / 21卷
关键词：
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this contribution, a Genetic Programming (GP) algorithm is used to develop empirical models of chemical process systems. GP performs symbolic regression, determining both the structure and the complexity of a model. Initially, steady-state model development using a GP algorithm is considered, next the methodology is extended to the development of dynamic input-output models. The usefulness of the technique is demonstrated by the development of inferential estimation models for two typical processes: a vacuum distillation column and a twin screw cooking extruder.
引用
收藏
页码：S1161 / S1166
页数：6
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