Performance monitoring of an industrial boiler: classification of relevant variables with Random Forests
نویسندگان
چکیده
A data mining methodology, the random forests, is applied to analyze pollutant emission 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 output variations.
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