Supervised learning for a Kraft recovery boiler: a data mining approach with Random Forests.

A data mining methodology, the random forests, is applied to predict high pressure steam
production from the recovery boiler of a Kraft pulping process. Starting from a large database of raw process data, the goal is to identify the input variables that explain the most significant output variations and to predict the high pressure steam flow.