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- W2350894757 abstract "There were 52 groups of the actual measured calorific value,water content and ash content data for the collected coal conducted.The linear regression and the artificial neural network were applied to predict the calorific value of coal.The data analysis showed that there was a good related relationship between the coal calorific value and ash content.In the linear regression prediction,the standard regression coefficient of the ash content was-0.90 and the standard regression coefficient of the moisture content was-0.33.The ash content would have more influences to the calorific value than the moisture content.The average absolute error of the predicted results was 0.27.In the MATLAB environment,the neural network toolbox was applied to establish the 2-5-1 neural network model and the average absolute error of the artificial neural network model was 0.22.In comparison between the coal calorific value predicted with the linear regression and the artificial neural network and the actual measured value,two predication methods could meet the actual requirements in a certain accurate area.The comprehensive compared results showed that the artificial neural network method could be applied to treat the non-linear data and could have the self study,self flexibility,allowing-error,high predicted result accuracy and other advantages." @default.
- W2350894757 created "2016-06-24" @default.
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- W2350894757 date "2009-01-01" @default.
- W2350894757 modified "2023-09-24" @default.
- W2350894757 title "Coal Calorific Value Prediction with Linear Regression and Artificial Neural Network" @default.
- W2350894757 hasPublicationYear "2009" @default.
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