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EnglishIn the paper a Soft Sensor design strategy for an industrial process, via neural NMA model, is described. A general design strategy, based on the automatic selection of regressors of a NAM model is proposed. It is based on the minimization of the cost function of a Gath Geva clustering algorithm. The obtained soft sensor will be implemented in a refinery in order to replace the measurement device during maintenance to guarantee continuity in the monitoring and control of the plant.
| Titolo: | Soft Sensor design for a Sulfur Recovery Unit using a clustering based approach |
| Autori: | |
| Data di pubblicazione: | 2008 |
| Abstract: | In the paper a Soft Sensor design strategy for an industrial process, via neural NMA model, is described. A general design strategy, based on the automatic selection of regressors of a NAM model is proposed. It is based on the minimization of the cost function of a Gath Geva clustering algorithm. The obtained soft sensor will be implemented in a refinery in order to replace the measurement device during maintenance to guarantee continuity in the monitoring and control of the plant. |
| Handle: | http://hdl.handle.net/11570/1906378 |
| ISBN: | 9781424415403 |
| Appare nelle tipologie: | 14.d.3 Contributi in extenso in Atti di convegno |
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http://hdl.handle.net/11570/1906378
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