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- W2367780959 abstract "The Artificial Neural Network(ANN) model of Self Organization Feature Map(SOM) and BP network were introduced to set up the model of steam turbine power output,with the aid of SOM's clustering ability,the limitation of conventional collection of training samples were addressed.Based on the actual operating data in 125 MW unit of Hefei Power Plant,with the trained model,the error of the power output predicted by this model and the actual power generated by steam turbine is less 1.5%,most of which is no more than 1%.With the established ANN models of steam turbine power output and the power needed in circulating water system,the optimum vacuum value(reference value) of condenser as well as the energy loss deviation of several main operation parameters from reference can be determined.Compared with conventional model,the model established in this paper is of good pertinence to equipment as a result of practical sampling data collection on running equipment." @default.
- W2367780959 created "2016-06-24" @default.
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- W2367780959 date "2005-01-01" @default.
- W2367780959 modified "2023-09-24" @default.
- W2367780959 title "Modeling and application of ANN models for power output of steam turbine and power consumption in circulating water system" @default.
- W2367780959 hasPublicationYear "2005" @default.
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