Prediction of water chemical properties in the cycle of a coal power plant using artificial neural networks
link https://doi.org/10.1109/IJCNN.1998.687163account_box Sáez Hueichapan, Doris Andreaaccount_box Sanz-Bobi, M. A.account_box Cipriano, Aldo
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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.
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| Autor | Sáez Hueichapan, Doris Andrea Sanz-Bobi, M. A. Cipriano, Aldo |
| Título | Prediction of water chemical properties in the cycle of a coal power plant using artificial neural networks |
| ISSN | 1098-7576 |
| ISBN | 780348591 |
| Fecha de publicación | 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. |
| Derechos | acceso restringido |
| DOI | 10.1109/IJCNN.1998.687163 |
| Editorial | IEEE |
| Enlace | https://doi.org/10.1109/IJCNN.1998.687163 |
| Palabra clave | Water Chemicals Power generation Input variables Predictive models Power system modeling Neural networks Artificial neural networks Fault detection Equations |
| Publicado en / Colección | IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (1998 : Anchorage, AK, Estados Unidos) |
| Tipo de documento | comunicación de congreso |