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

No Thumbnail Available
Date
1998
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
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.
Description
Keywords
Water, Chemicals, Power generation, Input variables, Predictive models, Power system modeling, Neural networks, Artificial neural networks, Fault detection, Equations
Citation
URI
https://doi.org/10.1109/IJCNN.1998.687163
 https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=687163
 https://repositorio.uc.cl/handle/11534/64075
Collections
Artículos de conferencia