Study on the Impact of Catalyst Factors on Ethanol Conversion and C4 Olefin Selectivity Based on Random Forest Regression

Optimizing catalyst combinations for efficient Ethanol Conversion and selective generation of C4 Olefins is important for resource conservation and environmental protection. Specifically, this study started from the temperature data in the catalysts. Firstly, the data were preprocessed to unify the temperature intervals using Hermite interpolation, and then Pearson correlation coefficients were used to further determine the linear relationship between the Ethanol Conversion rate and the C4 Olefin selectivity, respectively, and the temperature. On this basis, a random forest regression model was established to explore the importance of each catalytic factor on ethanol conversion rate and C4 olefin selectivity. Finally, multifactor ANOVA was used in this paper to explore the degree of influence of each catalytic factor on ethanol conversion and C4 olefin selectivity. In this study, it was found that for ethanol conversion rate, the F-value of ethanol concentration was 594.66, which was the largest compared to the other catalyst factors, indicating that it had the greatest influence on ethanol conversion rate.