Abstract

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Title:: Prediction Model of Compressive Strength of Lithium Slag Concrete Based on SPSS Regression Analysis

Author(s):: XU Kai-cheng; BI Li-ping; CHEN Meng-cheng; School of Civil Engineering and Architecture, East China Jiaotong University

Keywords:: SPSS; stepwise regression analysis; nonlinear regression; lithium slag concrete; compressive strength; residual analysis

Abstract:: The strength prediction model of lithium slag concrete was established by the stepwise regression method and multiple nonlinear regression analysis method in SPSS software. Then the residual plots and comparison between predicted and experimental values of the proposed models were analyzed. Combined with root mean square error, mean absolute error, mean absolute percentage error and model determination coefficient value, the accuracy of the proposed model was evaluated synthetically, and the better strength prediction model of lithium slag concrete was determined. The results show that the effects of waterbinder ratio, the amount of lithium slag and water reducing agent on the strength of lithium slag concrete are very significant. By the residual analysis and 95% predictive value interval test, the 5 proposed models have good accuracy. Based on the comprehensive evaluation, it is recommended that the best strength prediction model of lithium slag concrete is a nonlinear regression equation with the strength of cement, the binderwater ratio, the amount of lithium slag and water reducing agent as the independent variable, and its corresponding performance measurement values include that determination coefficient ?R² is 0.920, root mean square error is 3.684, mean absolute error is ?3.15, mean absolute percentage error is 5.44.