Please use this identifier to cite or link to this item:
http://hdl.handle.net/11531/87564| Title: | Prediction of water chemical properties in the cycle of a coal power plant using artificial neural networks |
| Authors: | Sáez, Doris Sanz Bobi, Miguel Ángel Cipriano, Aldo |
| Issue Date: | 9-May-1998 |
| Publisher: | Sin editorial (Anchorage, Estados Unidos de América) |
| 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. 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: | Capítulos en libros |
| URI: | http://hdl.handle.net/11531/87564 |
| Appears in Collections: | Artículos |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| IIT-98-003A.pdf | 480,34 kB | Adobe PDF | View/Open Request a copy |
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