Corrections to “Data Mode Related Interpretable Transformer Network for Predictive Modeling and Key Sample Analysis in Industrial Processes”

In [1], to maintain the integrity of the publication and uphold academic standards, a correction is requested for an identified error. Fig. 12 in the article is a duplicate of Fig. 13 due to an inadvertent mistake during the final stages of manuscript preparation.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Industrial Informatics
Published
2025-04-01
DOI
https://doi.org/10.1109/tii.2024.3402788
Primary Topic
Fault Detection and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Corrections to “Data Mode Related Interpretable Transformer Network for Predictive Modeling and Key Sample Analysis in Industrial Processes”

Xiaofeng Yuan, Chenliang Liu, Diju Liu, Weihua Gui et al.
IEEE Transactions on Industrial Informatics
Fault Detection and Control Systems
article

Corrections to “Data Mode Related Interpretable Transformer Network for Predictive Modeling and Key Sample Analysis in Industrial Processes”

Xiaofeng Yuan, Chenliang Liu, Diju Liu, Weihua Gui, Yalin Wang, Chunhua Yang
article en

Abstract

In [1], to maintain the integrity of the publication and uphold academic standards, a correction is requested for an identified error. Fig. 12 in the article is a duplicate of Fig. 13 due to an inadvertent mistake during the final stages of manuscript preparation.

IEEE Transactions on Industrial InformaticsVol. 21(4)
Central South University (CN)
Openalex Percentile: Top 93%
Fault Detection and Control Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.