Variable Correlation Analysis-Based Convolutional Neural Network for Far Topological Feature Extraction and Industrial Predictive Modeling-Reference-Cited by-同舟云学术

Variable Correlation Analysis-Based Convolutional Neural Network for Far Topological Feature Extraction and Industrial Predictive Modeling

Published:2024 Issue: Volume:73 Page:1-10
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Yuan Xiaofeng¹^ORCID,Wang Yichen¹^ORCID,Wang Chen¹^ORCID,Ye Lingjian²^ORCID,Wang Kai¹^ORCID,Wang Yalin¹^ORCID,Yang Chunhua¹^ORCID,Gui Weihua¹^ORCID,Shen Feifan³^ORCID

Affiliation:

1. School of Automation, Central South University, Hunan, Changsha, China

2. School of Engineering, Huzhou University, Huzhou, China

3. School of Information Science and Engineering, NingboTech University, Ningbo, China

Funder

Program of National Natural Science Foundation of China

CAAI-Huawei MindSpore Open Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10458995.pdf?arnumber=10458995

Reference35 articles.

1. Attention-Based Interval Aided Networks for Data Modeling of Heterogeneous Sampling Sequences With Missing Values in Process Industry

2. Multiscale Dynamic Feature Learning for Quality Prediction Based on Hierarchical Sequential Generative Network

3. A systematic approach for soft sensor development

4. Soft Sensors Based on Deep Neural Networks for Applications in Security and Safety

5. A Data-Driven Soft Sensor Modeling Method Based on Deep Learning and its Application

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