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 (United States of America). 04-09 mayo 1998

Summary:

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.

Keywords: 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

Publication date: May 1998.

Citation:
Sáez, D., Sanz-Bobi, M.A., Cipriano, A., 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 (United States of America). 04-09 May 1998.

IIT-98-003A