A dynamic CNN for nonlinear dynamic feature learning in soft sensor modeling of industrial process data-Reference-Cited by-同舟云学术

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A dynamic CNN for nonlinear dynamic feature learning in soft sensor modeling of industrial process data

Published:2020-11 Issue: Volume:104 Page:104614
ISSN:0967-0661
Container-title:Control Engineering Practice
language:en
Short-container-title:Control Engineering Practice

Author:

Yuan Xiaofeng,Qi Shuaibin,Wang Yalin,Xia Haibing

Funder

National Natural Science Foundation of China

National Key R&D Program of China

Natural Science Foundation of Hunan Province of China

Central South University, China

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Reference45 articles.

1. Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks;Abdeljaber;Journal of Sound and Vibration,2017

2. A distributed PCA-TSS based soft sensor for raw meal fineness in VRM system;Bao;Control Engineering Practice,2019

3. Temperature prediction model for Roller Kiln by ALD-based double locally weighted kernel principal component regression;Chen;IEEE Transactions on Instrumentation And Measurement,2018

4. Temperature prediction for roller kiln based on hybrid first-principle model and data-driven MW-DLWKPCR model;Dai;ISA Transactions,2020

5. Process data analytics via probabilistic latent variable models: A tutorial review;Ge;Industrial & Engineering Chemistry Research,2018

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