DSTED: A Denoising Spatial–Temporal Encoder–Decoder Framework for Multistep Prediction of Burn-Through Point in Sintering Process
Author:
Affiliation:
1. State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/41/9768205/09720102.pdf?arnumber=9720102
Reference32 articles.
1. Hierarchical Intelligent Control System and Its Application to the Sintering Process
2. Neural machine translation by jointly learning to align and translate;bahdanau;Proc 3rd Int Conf Learn Representations Conf Track Proc,2015
3. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
4. Power System Dynamic Model Reduction Based on Extended Krylov Subspace Method
5. BTP prediction of sintering process by using multiple models
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