Abstract
In this paper, the optimal catalyst combination and temperature were obtained by using multiple linear regressions using polarization, curve fitting, and regression analysis to prepare C4 olefins with optimal yields. Firstly, the investigation direction was outlined to explore different catalyst combinations and study the relationship with ethanol conversion, C4 olefin selectivity and temperature. In addition to this, the temperature linkage with different catalysts was added to analyze the catalyst components that have the greatest effect at different temperatures and the catalyst components that have the least effect. In addition, the optimal catalyst combination and temperature were further selected to optimize the yield of C4 olefins under the same experimental conditions, and the solved multiple regression equations were used as the constraint variables to establish the particle swarm algorithm model, and finally, MATLAB software was used to program the optimal catalyst composition parameters and temperature data.
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