2009Shandong MetallurgyRequires access

Prediction of Coke Strength Based on Multiple Linear Regression Analysis

Wu Xianxi

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Abstract

Coke strength was predicted by selecting the indexes of blending coal quality.The indexes were used as independent variables for multiple linear regression analysis and got regression models.Then took regression coefficient to make t test,eliminated the no significant index and renewed to make the linear regression models.The research indicated that the model can be used to effectively predict coke strength and the relative error forecasting results was within 5%.

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What this paper is about

Coke strength was predicted by selecting the indexes of blending coal quality.The indexes were used as independent variables for multiple linear regression analysis and got regression models.Then took regression coefficient to make t test,eliminated the no significant index and renewed to make the linear regression models.The research indicated that the model can be used to effectively predict coke strength and the relative error forecasting results was within 5%.

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Available abstract

Coke strength was predicted by selecting the indexes of blending coal quality.The indexes were used as independent variables for multiple linear regression analysis and got regression models.Then took regression coefficient to make t test,eliminated the no significant index and renewed to make the linear regression models.The research indicated that the model can be used to effectively predict coke strength and the relative error forecasting results was within 5%.

Key concepts: Linear regression, Regression analysis, Coke, Proper linear model, Statistics, Regression, Regression dilution, Coefficient of determination

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