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- Title
数据挖掘方法在汽油辛烷值损失计算中的应用.
- Authors
吴苹; 钟仪华; 雍雪; 张茜
- Abstract
Aiming at the key problem of reducing the octane loss in gasoline cleaning, a data mining-based octane loss calculation method is proposed. Firstly, various factors affecting the octane loss were analyzed. Then as an example a petrochemical company, the data provided by it was preprocessed reasonably and effectively through applying data mining methods. Secondly, feature extraction for multiple complex influencing factors was performed reasonably, and successfully extracted that 28 representative factors of affecting octane loss. Then mining modeling methods such as support vector machine regression, neural networks and random forests and cross-validation to train models were used to predict octane loss. Finally, through experiments and result analysis, it is shown that the random forest model based on data mining method can more accurately predict the octane loss, and has shown strong ability in feature extraction of influence factors and the prediction calculation on octane loss and can better serve the gasoline cleaning.
- Publication
Science Technology & Engineering, 2022, Vol 22, Issue 10, p4046
- ISSN
1671-1815
- Publication type
Article