A novel self-supervised deep LSTM network for industrial temperature prediction in aluminum processes application

Residual wide-kernel deep convolutional auto-encoder for intelligent rotating machinery fault diagnosis with limited samples

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End-to-end novel visual categories learning via auxiliary self-supervision

(2021) Yuanyuan Qing et al.   NEURAL NETWORKS

Soft sensor validation for monitoring and resilient control of sequential subway indoor air quality through memory-gated recurrent neural networks-based autoencoders

(2020) Jorge Loy-Benitez et al.   CONTROL ENGINEERING PRACTICE

An improved cell situation identification approach with convolutional neural network and wavelet extreme learning machine

(2020) Yongxiang Lei et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING

Unsupervised feature learning for self-tuning neural networks

(2020) Jongbin Ryu et al.   NEURAL NETWORKS

A hybrid model combining mechanism with semi-supervised learning and its application for temperature prediction in roller hearth kiln

(2020) Jiayao Chen et al.   JOURNAL OF PROCESS CONTROL

A semi-supervised Laplacian extreme learning machine and feature fusion with CNN for industrial superheat identification

(2019) Yongxiang Lei et al.   NEUROCOMPUTING

Nonlinear Dynamic Soft Sensor Modeling With Supervised Long Short-Term Memory Network

(2019) Xiaofeng Yuan et al.   IEEE Transactions on Industrial Informatics

Time series forecasting of petroleum production using deep LSTM recurrent networks

(2018) Alaa Sagheer et al.   NEUROCOMPUTING