@inproceedings{67b0e252232244ed9ad2039981caf3a0,
title = "Research on Optimization Method of C4 Olefins Preparation by Ethanol Coupling Based on Machine Learning Model",
abstract = "As an important chemical raw material, C4 olefins are widely used in the manufacture of chemical products and pharmaceutical intermediates. In this paper, a machine learning model is established by quantifying the catalyst combination and temperature conditions in the process of preparing C4 olefins. Finally, the optimization scheme of ethanol coupling production of C4 olefins based on machine learning model was obtained. A relational function machine learning model based on CatBoostRegressor integrated regression was established to fit the relationship between different catalyst compositions and temperatures and the yield of C4 olefins. Then, all possible results were quantitatively searched and analyzed through the grid search algorithm, and the combinations of catalyst and temperatures that maximizes the yield of C4 olefins is obtained. This paper finally obtained the optimal plan for the preparation of C4 olefins.",
keywords = "C4 Olefins preparation, grid search, linear regression model, machine learning",
author = "Caijun Jia and Shitong Liu and Jiayu Li and Yanhong Yuan and Yapeng Wang and Im, {Sio Kei} and Linjun Wang and Xuming Tong",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 9th International Conference on Computer and Communications, ICCC 2023 ; Conference date: 08-12-2023 Through 11-12-2023",
year = "2023",
doi = "10.1109/ICCC59590.2023.10507352",
language = "English",
series = "2023 9th International Conference on Computer and Communications, ICCC 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2207--2211",
booktitle = "2023 9th International Conference on Computer and Communications, ICCC 2023",
address = "United States",
}