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- W1587948080 abstract "Abstract In this paper, neural networks approaches are compared for predicting the high pressure (HP) steam flow rate from a Kraft recovery boiler. We apply two types of neural networks: a static multilayer perceptron and a dynamic Elman's recurrent neural network. Starting from a one-day database of raw process data related to the boiler, the goal is to model and predict the next 12-hours of HP steam flow production from the boiler to the steam turbine. The results illustrate the potential of the dynamic approach in this task." @default.
- W1587948080 created "2016-06-24" @default.
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- W1587948080 date "2011-01-01" @default.
- W1587948080 modified "2023-10-04" @default.
- W1587948080 title "Recurrent neural network prediction of steam production in a Kraft recovery boiler" @default.
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- W1587948080 doi "https://doi.org/10.1016/b978-0-444-54298-4.50135-5" @default.
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