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Prediction of gaseous emissions from industrial stacks using an artificial intelligence method
Anghel, C. I. and Ozunu, A. Prediction of gaseous emissions from industrial stacks using an artificial intelligence method Chemical Papers, Vol.60, No. 6, 2006, 410-415
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Document type:
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Článok z časopisu / Journal Article |
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Collection:
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Chemical papers
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| Author(s) |
Anghel, C. I.
Ozunu, A.
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| Title |
Prediction of gaseous emissions from industrial stacks using an artificial intelligence method
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| Journal name |
Chemical Papers
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| Publication date |
2006
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| Year available |
2006
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| Volume number |
60
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| Issue number |
6
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| ISSN |
0366-6352
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| Start page |
410
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| End page |
415
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| Place of publication |
Poland
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| Publisher |
Versita
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| Collection year |
2006
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| Language |
english
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| Subject |
290000 Engineering and Technology
290600 Chemical Engineering
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| Abstract/Summary |
A novel technique based on artificial intelligence methods able to predict pollutant emission concentrations from industrial stacks is presented. This procedure combines regression and classification problems into a unified technique, named minimax decision procedure. The core of this procedure is based on the minimax probability machine regression model. Using experimental databases, the trend of pollutant emissions and the level of pollution for one industrial thermal power station stack were presented. Based on this unified technique, numerical experiments provided the estimates of concentrations of CO, NOx, NO, and SO2 confirming the predictive power of this procedure.
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