{"title":"基于注意驱动卷积神经网络的偶联反应产率回归预测","authors":"Hexun Hou, Hengzhe Wang, Yanhui Guo, Puyu Zhang, Lichao Peng, Xiaohui Yang","doi":"10.46793/match.89-1.199h","DOIUrl":null,"url":null,"abstract":"The traditional method to improve the yield of Buchwald-Hartwig cross coupling reaction is to change the reactants or reaction conditions, but the reaction has many problems, such as harsh reaction conditions, complex synthetic route. In 2018, Doyle reported a yield prediction method based on random forest in Science. However, the predicted value of the regression tree in the random forest is the average value of the target variable of the leaf node, which treats the feature as equally important. We focused on the important characteristic information in order to obtain a more accurate yield prediction value. Therefore, it is of interest to apply some advanced deep learning methods to the performance prediction of chemical reactions, during which less training data may be required.","PeriodicalId":51115,"journal":{"name":"Match-Communications in Mathematical and in Computer Chemistry","volume":"65 19","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Regression Prediction of Coupling Reaction Yield Based on Attention-Driven Convolutional Neural Network\",\"authors\":\"Hexun Hou, Hengzhe Wang, Yanhui Guo, Puyu Zhang, Lichao Peng, Xiaohui Yang\",\"doi\":\"10.46793/match.89-1.199h\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The traditional method to improve the yield of Buchwald-Hartwig cross coupling reaction is to change the reactants or reaction conditions, but the reaction has many problems, such as harsh reaction conditions, complex synthetic route. In 2018, Doyle reported a yield prediction method based on random forest in Science. However, the predicted value of the regression tree in the random forest is the average value of the target variable of the leaf node, which treats the feature as equally important. We focused on the important characteristic information in order to obtain a more accurate yield prediction value. Therefore, it is of interest to apply some advanced deep learning methods to the performance prediction of chemical reactions, during which less training data may be required.\",\"PeriodicalId\":51115,\"journal\":{\"name\":\"Match-Communications in Mathematical and in Computer Chemistry\",\"volume\":\"65 19\",\"pages\":\"\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2022-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Match-Communications in Mathematical and in Computer Chemistry\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.46793/match.89-1.199h\",\"RegionNum\":2,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Match-Communications in Mathematical and in Computer Chemistry","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.46793/match.89-1.199h","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Regression Prediction of Coupling Reaction Yield Based on Attention-Driven Convolutional Neural Network
The traditional method to improve the yield of Buchwald-Hartwig cross coupling reaction is to change the reactants or reaction conditions, but the reaction has many problems, such as harsh reaction conditions, complex synthetic route. In 2018, Doyle reported a yield prediction method based on random forest in Science. However, the predicted value of the regression tree in the random forest is the average value of the target variable of the leaf node, which treats the feature as equally important. We focused on the important characteristic information in order to obtain a more accurate yield prediction value. Therefore, it is of interest to apply some advanced deep learning methods to the performance prediction of chemical reactions, during which less training data may be required.
期刊介绍:
MATCH Communications in Mathematical and in Computer Chemistry publishes papers of original research as well as reviews on chemically important mathematical results and non-routine applications of mathematical techniques to chemical problems. A paper acceptable for publication must contain non-trivial mathematics or communicate non-routine computer-based procedures AND have a clear connection to chemistry. Papers are published without any processing or publication charge.