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- W2363669607 abstract "According to the practical production process of hot metal pretreatment,a model was established to predict the nitrogen content of hot metal in desulphurization pretreatment by BP artificial neural network.After training the network using production data,the model can predict the nitrogen content of hot metal in desulphurization pretreatment,the relative prediction error can be controlled under 22%,and the absolute error is below 8×10-4%.Changing the values of input parameters and calculating,the result indicates that the initial temperature nitrogen content,carbon content and phosphorus content have the maximum influence.The temperature and carbon content are of negative effect,and the nitrogen content has positive effect.High temperature and carbon content are favorable to denitrification." @default.
- W2363669607 created "2016-06-24" @default.
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- W2363669607 date "2007-01-01" @default.
- W2363669607 modified "2023-09-24" @default.
- W2363669607 title "Nitrogen content prediction in hot metal desulphurization pretreatment" @default.
- W2363669607 hasPublicationYear "2007" @default.
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