| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 772912 | Energy Conversion and Management | 2007 | 8 Pages |
The optimization of operational parameters in control systems requires the application of a mathematical model of the investigated process. Analytical models are usually complicated and time-consuming. For optimization purposes more convenient are empirical models which express the main characteristic of the behaviour of the investigated process. One of the basic methods of empirical modelling is the application of neural networks.The paper presents the results of the application of neural modelling to identify the energy characteristics of a Cowper stove. The results of numerical experiment have been obtained basing on the analytical model of a Cowper stove. The estimation of parameters of the neural model of a Cowper stove has been carried out by means of the back-propagation method.
