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- W2566781041 abstract "Paper manufacturing is energy demanding and improved modelling of the pulp bleach process is the main non-invasive means of reducing energy costs. In this paper, time it takes to bleach paper pulp to desired brightness is examined. The model currently used is analysed and benchmarked against two machine learning models Random Forest and TreeBoost. Results suggests that the current model can be superseded by the machine learning models and it does not use the optimal compact subset of features. Despite the differences between the machine learning models, a feature ranking correlation has been observed for the new models. One novel, yet unused, feature that both machine learning models found to be important is the concentration of bleach agent." @default.
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- W2566781041 date "2016-01-01" @default.
- W2566781041 modified "2023-10-06" @default.
- W2566781041 title "Feature Selection and Bleach Time Modelling of Paper Pulp Using Tree Based Learners" @default.
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- W2566781041 doi "https://doi.org/10.1007/978-3-319-48743-4_31" @default.
- W2566781041 hasPublicationYear "2016" @default.
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