Zliobaite, I., Bakker, J. and Pechenizkiy, M., 2009. OMFP: An Approach for Online Mass Flow Prediction in CFB Boilers. In: the 12th International Conf. on Discovery Science (DS 2009), pp. 272-286.
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Official URL: http://www.springerlink.com/content/51412317675482...
Fuel feeding and inhomogeneity of fuel typically cause process fluctuations in the circulating fluidized bed (CFB) boilers. If control systems fail to compensate the fluctuations, the whole plant will suffer from fluctuations that are reinforced by the closed-loop controls. Accurate estimates of fuel consumption among other factors are needed for control systems operation. In this paper we address a problem of online mass flow prediction. Particularly, we consider the problems of (1) constructing the ground truth, (2) handling noise and abrupt concept drift, and (3) learning an accurate predictor. Last but not least we emphasize the importance of having the domain knowledge concerning the considered case. We demonstrate the performance of OMPF using real data sets collected from the experimental CFB boiler.
|Item Type:||Conference or Workshop Item (Paper)|
|Additional Information:||Lecture Notes in Computer Science, 2009, Volume 5808/2009, 272-286|
|Subjects:||Generalities > Computer Science and Informatics > Artificial Intelligence|
|Group:||School of Design, Engineering & Computing > Smart Technology Research Centre|
|Deposited By:||Dr Indre Zliobaite LEFT|
|Deposited On:||25 Oct 2011 13:51|
|Last Modified:||07 Mar 2013 15:49|
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