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Study on thermal-hydraulic performance of printed circuit heat exchangers with supercritical methane based on machine learn ... 1 1 Introduction 1 2 Methodology 2 2.1 Physical model and data 2 2.2 Machine learning algorithms 4 2.2.1 Artificial neural networks (ANN) 4 2.2.2 Extreme gradient boosting (XGBoost) 5 2.2.3 Light gradient boosting machine (LightGBM) 5 2.2.4 Random forest 5 2.3 Error analysis 6 2.4 Data preprocessing 6 2.4.1 Data splitting 6 2.4.2 Standardization 6 2.4.3 Parameter analysis 6 2.5 One-dimensional simulation 6 3 Results and discussion 7 3.1 Data partitioning 7 3.2 Hyperparameters optimization 8 3.2.1 Architecture selection of ANN 8 3.2.2 Parameter optimization of other models 9 3.3 Model performance comparison 9 3.4 Performance evaluation of the ANN model 10 3.5 One-dimensional simulation results 13 4 Conclusions 14 Credit author statement 16 Declaration of competing interest 16 Data availability 16 Acknowledgements 16 References 16

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Language

UND

Category

nonfiction