Neural Networks as a Tool for Gray Box Modelling in Reactive Distillation
In this paper we discuss the use of neural networks as a tool for gray box modelling of the reactive distillation column. The basic idea is to replace certain correlations for the calculation of physical properties by neural networks. Different architectures as radial basis function networks and fee...
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| creator | Dadhe, Kai Roßmann, Volker Durmus, Kazim Engell, Sebastian |
| description | In this paper we discuss the use of neural networks as a tool for gray box modelling of the reactive distillation column. The basic idea is to replace certain correlations for the calculation of physical properties by neural networks. Different architectures as radial basis function networks and feedforward networks are compared and their approximation abilities are demonstrated. |
| doi_str_mv | 10.1007/3-540-45493-4_58 |
| format | Book Chapter |
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| fulltext | fulltext |
| identifier | ISSN: 0302-9743 |
| ispartof | Computational Intelligence. Theory and Applications, 2001, Vol.2206, p.576-588 |
| issn | 0302-9743 1611-3349 |
| language | eng |
| recordid | cdi_pascalfrancis_primary_14044594 |
| source | Springer Books |
| subjects | Applied sciences Artificial intelligence Computer science control theory systems Connectionism. Neural networks Distillation Column Exact sciences and technology Hide Layer Model Predictive Control Radial Basis Function Root Mean Square Error |
| title | Neural Networks as a Tool for Gray Box Modelling in Reactive Distillation |
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