Construction of a Machine Learning-Based Model for Predicting the Mechanical Properties of \text-\mathrm-\text-\text System Steels

In order to improve the prediction accuracy of mechanical properties of Fe-C-Mn-Al steel, XGBoost, LightGBM and deep neural network (DNN) models are constructed based on the experimental data, and feature engineering optimization, hyper-parameter tuning, and confidence-weighted integration strategie...

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Bibliographic Details
Main Authors: Zhang, Lijuan, Ge, Xinye, Liu, Xia, Liu, Zhaoqin, Guo, Feng
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Artificial neural networks
Computational modeling
Data models
Elongation
Fe-C-Mn-Al system steel
feature engineering
machine learning
Mechanical factors
mechanical property prediction
Optimization
Predictive models
Steel
Tuning
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