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- W1597626033 abstract "In this paper, with a 1000MW ultra-supercritical (USC) unit as the object investigated, its superheated steam temperature characteristic was studied. Based on the operating data which were extracted from a full-scope simulator of the given USC power unit, the BP RBF and Elman neural networks were respectively used to establish the model of superheated steam temperature characteristic. There were ten input variables, including main steam pressure, fuel flow, total air flow, feedwater flow, etc. The output was superheated steam temperature. The simulation test results verified the validity of the three models." @default.
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- W1597626033 date "2015-05-01" @default.
- W1597626033 modified "2023-09-22" @default.
- W1597626033 title "The simulation research and neural network modeling of superheated steam temperature characteristics for ultra-supercritical unit" @default.
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- W1597626033 doi "https://doi.org/10.1109/ccdc.2015.7162337" @default.
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