Prediction of PEMFC life based on IGJO-TCN-BiGRU-Attention.

Jun Zhao, Hang Shang, Yongpeng Shen, Pengbin Zhang, Xiaoliang Yang, Pu Liu

Abstract read

In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jun ZhaoCollege of Electronic and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450000, China.

Hang ShangCollege of Electronic and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450000, China. 332301060118@zzuli.edu.cn.

Yongpeng ShenCollege of Electronic and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450000, China. shenyongpeng@zzuli.edu.cn.

Pengbin ZhangCollege of Electronic and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450000, China.

Xiaoliang YangCollege of Electronic and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450000, China.

Pu LiuCollege of Electronic and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450000, China.

Funding

National Natural Science Foundation of China General Program 62273313

6 · The paper itself

Abstract

To accurately predict the life of proton exchange membrane fuel cells (PEMFC), the IGJO-TCN-BiGRU-Attention algorithm is proposed, which integrates an intelligent optimization algorithm into a deep learning framework. Temporal convolutional network (TCN) decodes spatial correlations in voltage-temperature parameters. Bidirectional gated recurrent units (BiGRU) models performance degradation dynamics. Attention mechanism makes the model focus on the part that contributes the most to the predicted outcome. The improved golden jackal optimization (IGJO) algorithm proposed in this work is employed to optimize the learning rate, L

Indexed as

Bidirectional gated recurrent unitImproved Golden Jackal AlgorithmProton exchange membrane fuel cellSelf-Attention mechanismTemporal convolutional neural network

Identifiers

PMID41326586

DOI10.1038/s41598-025-29800-x

PMCPMC12770459

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.