A Bidirectional Attention-Based LSTM Model for Multi-Step Ahead Prediction in Dynamic Soft Sensors
Author:
Affiliation:
1. School of Engineering, Huzhou University,Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems,Huzhou,China,313000
Funder
National Natural Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10606543/10606546/10606926.pdf?arnumber=10606926
Reference19 articles.
1. Data-driven soft sensors in blast furnace ironmaking: a survey
2. Deep Learning-Based Feature Representation and Its Application for Soft Sensor Modeling With Variable-Wise Weighted SAE
3. Dynamic historical information incorporated attention deep learning model for industrial soft sensor modeling
4. Ensemble models with uncertainty analysis for multi-day ahead forecasting of chlorophyll a concentration in coastal waters
5. Information Complementary Fusion Stacked Autoencoders for Soft Sensor Applications in Multimode Industrial Processes
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