[en] Machine learning techniques are compared
to predict nitrogen oxide (NOx) pollutant
emission from the recovery boiler of a Kraft
pulp mill. Starting from a large database of
raw process data related to a Kraft recovery
boiler, we consider a regression problem in
which we are trying to predict the value of a
continuous variable. Generalization is done
on the worst case configuration possible to
make sure the model is adequate: the training
period concerns stationary operations while
test periods mainly focus on NOx emissions
during transient operations.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
