Rolling force prediction of hot-rolled transverse thickness-varying plates based on stochastic configuration network
Author:
Affiliation:
1. Northeastern University,The State Key Laboratory of Rolling and Automation,Shenyang,China
Funder
National Natural Science Foundation of China
Liaoning Revitalization Talents Program
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10326186/10327501/10327535.pdf?arnumber=10327535
Reference17 articles.
1. Robust stochastic configuration networks with kernel density estimation for uncertain data regression
2. Stochastic Configuration Networks Based Adaptive Storage Replica Management for Power Big Data Processing
3. Prediction and analysis of key parameters of head deformation of hot-rolled plates based on artificial neural networks
4. Point and interval prediction of the effective length of hot-rolled plates based on IBES-XGBoost
5. Stochastic configuration networks ensemble with heterogeneous features for large-scale data analytics
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