Prediction of water chemical properties in the cycle of a coal power plant using artificial neural networks

D. Sáez, M.A. Sanz-Bobi, A. Cipriano

IEEE International Joint Conference on Neural Networks - IJCNN 1998, Anchorage (Estados Unidos de América). 04-09 mayo 1998

Resumen:

Describes a systematic methodology based on artificial neural networks for model identification and its application to the prediction of water chemical properties under normal operation conditions in a power plant. The model obtained allows detection of incipient anomalies by comparison between the real and predicted values.

Palabras clave: Water , Chemicals , Power generation , Input variables , Predictive models , Power system modeling , Neural networks , Artificial neural networks , Fault detection , Equations

DOI: https://doi.org/10.1109/IJCNN.1998.687163

Publicado en IJCNN 98, pp: 1-6, ISBN: 0-7803-4859-1

Fecha de publicación: 1998-05-09.

Cita:
D. Sáez, M.A. Sanz-Bobi, A. Cipriano, Prediction of water chemical properties in the cycle of a coal power plant using artificial neural networks, IEEE International Joint Conference on Neural Networks - IJCNN 1998, Anchorage (Estados Unidos de América). 04-09 mayo 1998. En: IJCNN 98: Conference proceedings, ISBN: 0-7803-4859-1