CatBoost-Based Framework for Intelligent Prediction and Reaction Condition Analysis of Coupling Reaction

被引：0

作者：

Wang, Hengzhe ^{[1
]}

Peng, Lichao ^{[2
]}

Chang, Li ^{[3
]}

Li, Zixin ^{[1
]}

Guo, Yanhui ^{[1
]}

Li, Qian ^{[4
]}

Yang, Xiaohui ^{[1
]}

机构：

[1] Henan Univ, Sch Math & Stat, Henan Engn Res Ctr Artificial Intelligence Theory, Kaifeng 475000, Peoples R China

[2] Henan Univ, Natl & Local Joint Engn Res Ctr Appl Technol Hybr, Kaifeng 475000, Peoples R China

[3] Henan Univ, Henan Sci Res Platform Serv Ctr, Kaifeng 475000, Peoples R China

[4] Henan Univ, Inst Sci & Technol, Kaifeng 475000, Peoples R China

来源：

MATCH-COMMUNICATIONS IN MATHEMATICAL AND IN COMPUTER CHEMISTRY | 2023年 / 90卷 / 01期

关键词：

MACHINE; ISOXAZOLES; DRIVEN; MODELS;

D O I：

10.46793/match.90-1.053W

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

Machine learning is increasingly popular in predicting chemical reaction performance. This study aims to apply the CatBoost algorithm to build an intelligent prediction system for organic chemical reaction yields. The parameter analysis, convergence analysis, prediction accuracy analysis and generalization analysis are carried out. Then, the internal relationship between reaction conditions and yield is excavated through feature importance and SHAP. The results show that the proposed method has the potential as a high-precision tool to assist the optimization of chemical reaction system.

引用

页码：53 / 71

页数：19

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