An Ensemble-Learning Approach To Predict the Coke Yield of Commercial FCC Unit

Zhang，Mengxuan1; Cao，Daofan2; Lan，Xingying1; Shi，Xiaogang1; Gao，Jinsen1

2021

10.1021/acs.iecr.1c04735

INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH   影响因子和分区

0888-5885

1520-5045

This work proposes an ensemble learning-based catalytic cracking coke yield prediction model called the harmonic-ensembled extreme learning machine (HEELM). The model integrates extreme learning machine (ELM) base learners with different activation functions to improve the overall prediction effect. An overfitting index is proposed, and the optimal number of hidden layer nodes of ELM-base learners is determined with it. By examining the influence of different activation functions on the prediction results, the best activation function structure of the ELM-base learner has been determined. Besides, a harmonic layer is established to determine the weight of each base learner in real-time. The proposed model is validated using 1.5 years of historical data from China's commercial fluidized catalytic cracking (FCC) plant. The results show that the proposed model has outperformed most other ELM-base learners. The relative prediction error is further reduced by 10.97% after introducing the harmonic layer. The proposed model exhibits stable performance with good generalization in three segments of industrial data, and it has guiding significance for stable operation and CO2 emission reduction of the FCC plant.

EI

英语

其他

20221812046268

Chemical activation ; Coke ; Cracks ; Emission control ; Fluidization ; Forecasting ; Knowledge acquisition

Air Pollution Control:451.2 ; Solid Fuels:524 ; Artificial Intelligence:723.4 ; Chemical Reactions:802.2 ; Chemical Operations:802.3 ; Chemical Products Generally:804 ; Numerical Methods:921.6

CHEMISTRY

2-s2.0-85129060658

Scopus

1.State Key Laboratory of Heavy Oil Processing,China University of Petroleum-Beijing,Beijing,102249,China
2.Department of Chemistry and Clean Energy Institute,Southern University of Science and Technology,Shenzhen,518055,China

Zhang，Mengxuan,Cao，Daofan,Lan，Xingying,et al. An Ensemble-Learning Approach To Predict the Coke Yield of Commercial FCC Unit[J]. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH,2021,61:8422-8431.

Zhang，Mengxuan,Cao，Daofan,Lan，Xingying,Shi，Xiaogang,&Gao，Jinsen.(2021).An Ensemble-Learning Approach To Predict the Coke Yield of Commercial FCC Unit.INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH,61,8422-8431.

Zhang，Mengxuan,et al."An Ensemble-Learning Approach To Predict the Coke Yield of Commercial FCC Unit".INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH 61(2021):8422-8431.