RESEARCH ON THE PREPARATION AND PROCESS CONDITIONS OF C4 OLEFINS USING GREY PREDICTION MODEL AND MULTIPLE LINEAR REGRESSION MODEL

In recent years, with the rapid development of the organic industry, the demand for olefins has gradually increased, and the demand for C4 olefins is particularly significant. The preparation of C4 olefins has become a hot spot in the field of organic industry development. In order to study how to improve the yield of C4 olefins, this paper firstly takes ethanol conversion, C4 olefin selectivity, and C4 olefin yield as the research objects, quantifies them digitally, and constructs a multiple linear regression model, and then, with the help of the least square principle and Cramer rule, the multiple linear regression model is solved. Secondly, based on the grey system theory, using the temperature and catalyst type as raw data, we construct a grey prediction model. Finally, using the multiple linear regression model and the grey prediction model, considering the influencing factors of the actual production of C4 olefins, reasonable suggestions are given on how to choose the catalyst combination and temperature to improve the yield of C4 olefins in the actual production.