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Research on multiple regression -PSO algorithm for C4 olefin preparation

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DOI: 10.23977/jmpd.2021.050113 | Downloads: 2 | Views: 262


Huifang Chen 1, Qian Zhang 1


1 Jiangnan University, Wuxi, Jiangsu, 214122

Corresponding Author

Huifang Chen


In this paper, based on the experimental data of C4 olefin yield under different catalyst combinations and temperatures, the optimal experimental conditions for the preparation of olefin by ethanol catalytic coupling[1] were explored by establishing multiple regression model[2] and solving by particle swarm optimization algorithm. Firstly, Spearman correlation coefficients were calculated for each catalyst combination based on standardized data processing. It was found that ethanol conversion was positively correlated with C4 olefins selectivity and temperature under most preparation conditions. Then, multiple linear regression model was used to set experimental parameters and temperature range with C4 olefin yield as the objective function. Finally, particle swarm optimization algorithm was introduced to search for optimal solution.


PSO algorithm, Spearman correlation coefficient, multiple regression


Huifang Chen, Qian Zhang. Research on multiple regression -PSO algorithm for C4 olefin preparation. Journal of Materials, Processing and Design (2021) 5: 63-66. DOI:


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