Efficient JITL framework for nonlinear industrial chemical engineering soft sensing based on adaptive multi-branch variable scale integrated convolutional neural networks

Chen, Yifan; Li, Anlan; Li, Xiangyang; Xue, Dong; Long, Jian

doi:10.1016/j.aei.2023.102199

Advanced Engineering Informatics

2023

DOI: 10.1016/j.aei.2023.102199

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Efficient JITL framework for nonlinear industrial chemical engineering soft sensing based on adaptive multi-branch variable scale integrated convolutional neural networks

Yifan Chen,

Anlan Li,

Xiangyang Li

et al.

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Cited by 8 publications

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Efficient JITL framework for nonlinear industrial chemical engineering soft sensing based on adaptive multi-branch variable scale integrated convolutional neural networks

Cited by 8 publications

References 60 publications

A novel semi-supervised robust learning framework for dynamic generative latent variable models and its application to industrial virtual metrology

A novel semi-supervised robust learning framework for dynamic generative latent variable models and its application to industrial virtual metrology

Graph-based active semi-supervised learning: Case study in water quality monitoring

Efficient prediction framework for large-scale nonlinear petrochemical process based on feature selection and temporal-attention LSTM: Applied to fluid catalytic cracking

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