Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A Novel Deep Recurrent Belief Network Model for Trend Prediction of Transformer DGA Data
Bo Qi, Yiming Wang, Peng Zhang, et al.
IEEE Access (2019) Vol. 7, pp. 80069-80078
Open Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

Photoluminescence Spectroscopy Measurements for Effective Condition Assessment of Transformer Insulating Oil
Abdelrahman M. Alshehawy, Diaa‐Eldin A. Mansour, Mohsen Ghali, et al.
Processes (2021) Vol. 9, Iss. 5, pp. 732-732
Open Access | Times Cited: 76
Hybrid CEEMDAN-DBN-ELM for online DGA serials and transformer status forecasting
Weiliang Zeng, Yunfei Cao, Lutao Feng, et al.
Electric Power Systems Research (2023) Vol. 217, pp. 109176-109176
Closed Access | Times Cited: 18
Dynamic Fault Prediction of Power Transformers Based on Lasso Regression and Change Point Detection by Dissolved Gas Analysis
Jun Jiang, Ruyi Chen, Chaohai Zhang, et al.
IEEE Transactions on Dielectrics and Electrical Insulation (2020) Vol. 27, Iss. 6, pp. 2130-2137
Closed Access | Times Cited: 45
Fault diagnosis of transformer using artificial intelligence: A review
Yan Zhang, Yufeng Tang, Yongqiang Liu, et al.
Frontiers in Energy Research (2022) Vol. 10
Open Access | Times Cited: 23
Fuzzy Logic-Based Spectroscopic Analysis for Condition Assessment of Distribution Transformers
Nithin Raj, Dinesh Gopinath, B Aryanandiny, et al.
IEEE Transactions on Industry Applications (2024) Vol. 60, Iss. 3, pp. 4968-4977
Closed Access | Times Cited: 4
Computational intelligence for preventive maintenance of power transformers
Shen Yuong Wong, Xiaofeng Ye, Fengkai Guo, et al.
Applied Soft Computing (2021) Vol. 114, pp. 108129-108129
Closed Access | Times Cited: 30
Prediction of the dissolved gas concentration in power transformer oil based on SARIMA model
Jiaxin Liu, Zijian Zhao, Yuanchen Zhong, et al.
Energy Reports (2022) Vol. 8, pp. 1360-1367
Open Access | Times Cited: 21
Hybrid feature selection–artificial intelligence–gravitational search algorithm technique for automated transformer fault determination based on dissolved gas analysis
Hazlee Azil Illias, Kai Choon Chan, Hazlie Mokhlis
IET Generation Transmission & Distribution (2020) Vol. 14, Iss. 8, pp. 1575-1582
Open Access | Times Cited: 27
A Novel Self-Decision Fault Diagnosis Model Based on State-Oriented Correction for Power Transformer
Bo Qi, Yiming Wang, Peng Zhang, et al.
IEEE Transactions on Dielectrics and Electrical Insulation (2020) Vol. 27, Iss. 6, pp. 1778-1786
Closed Access | Times Cited: 19
Prediction for Dissolved Gas in Power Transformer Oil Based On TCN and GCN
Diansheng Luo, Jie Fang, Hongying He, et al.
IEEE Transactions on Industry Applications (2022) Vol. 58, Iss. 6, pp. 7818-7826
Closed Access | Times Cited: 11
Intelligent Deep Learning Method for Forecasting the Health Evolution Trend of Aero-Engine With Dispersion Entropy-Based Multi-Scale Series Aggregation and LSTM Neural Network
Wei Jiang, Nan Zhang, Xiaoming Xue, et al.
IEEE Access (2020) Vol. 8, pp. 34350-34361
Open Access | Times Cited: 16
Application of Statistical Distribution Models to Predict Health Index for Condition-Based Management of Transformers
Amran Mohd Selva, Norhafiz Azis, Nor Shafiqin Shariffudin, et al.
Applied Sciences (2021) Vol. 11, Iss. 6, pp. 2728-2728
Open Access | Times Cited: 13
Research on Transformer Condition Prediction Based on Gas Prediction and Fault Diagnosis
Can Ding, Wenhui Chen, Donghai Yu, et al.
Energies (2024) Vol. 17, Iss. 16, pp. 4082-4082
Open Access | Times Cited: 1
Grid Distribution Fault Occurrence and Remedial Measures Prediction/Forecasting through Different Deep Learning Neural Networks by Using Real Time Data from Tabuk City Power Grid
Fahad M. Almasoudi
Energies (2023) Vol. 16, Iss. 3, pp. 1026-1026
Open Access | Times Cited: 4
Data Restoration of dissolved gas content in transformer oil based on the CS-SVR model
Nana Wang, Jianqiu Li, Wenyi Li, et al.
Journal of Physics Conference Series (2024) Vol. 2703, Iss. 1, pp. 012078-012078
Open Access | Times Cited: 1
Enhancing Transformer Health Index Prediction Using Dissolved Gas Analysis Data Through Integration of LightGBM and Robust EM Algorithms
Aman Samson Mogos, Xiaodong Liang, C. Y. Chung
IEEE Access (2024) Vol. 12, pp. 108472-108483
Open Access | Times Cited: 1
Designing digitally enabled proactive maintenance systems in power distribution grids: A scoping literature review
Lasse Kappel Mortensen, Konrad Sundsgaard, Hamid Reza Shaker, et al.
Energy Reports (2024) Vol. 12, pp. 1-21
Open Access | Times Cited: 1
Review on Supervised and Unsupervised Learning Techniques for Electrical Power Systems: Algorithms and Applications
Songbo Chen
IEEJ Transactions on Electrical and Electronic Engineering (2021) Vol. 16, Iss. 11, pp. 1487-1499
Closed Access | Times Cited: 10
Improved BLS based transformer fault diagnosis considering imbalanced samples
Chao Xu, Xiaolan Li, Zhenhao Wang, et al.
Energy Reports (2022) Vol. 8, pp. 1446-1453
Open Access | Times Cited: 7
Optimal Data Selection Rule Mining for Transformer Condition Assessment
Peng Zhang, Bo Qi, Mengyu Shao, et al.
IEEE Access (2021) Vol. 9, pp. 156962-156972
Open Access | Times Cited: 5
A Novel Hybrid Model Combining Improved VMD and ELM with Extended Maximum Correntropy Criterion for Prediction of Dissolved Gas in Power Transformer Oil
Gang Du, Zhenming Sheng, Jiaguo Liu, et al.
Processes (2024) Vol. 12, Iss. 1, pp. 193-193
Open Access
Research on Key Technologies and Issues of Intelligent Operation and Maintenance Gateway for Substations
Linchuan Song, Xiaoming You, M. Liu
(2024) Vol. 46, pp. 1077-1082
Closed Access
A Novel Method to Estimate the Lifetime of Mineral Oil-type Power Transformers Based on the Analysis of Chemical and Physical Indicators Using Artificial Intelligence
Mohammad K K Alabdullh, Mahmood Joorabian, Seyyed Ghodratollah Seifossadat, et al.
Heliyon (2024) Vol. 10, Iss. 22, pp. e40447-e40447
Open Access
Fuzzy Logic Based Spectral Analysis for Condition Assessment of Transformer Oil
Nithin Raj, Dinesh Gopinath, B Aryanandiny, et al.
2022 IEEE IAS Global Conference on Emerging Technologies (GlobConET) (2023), pp. 1-6
Closed Access | Times Cited: 1
Forecasting top oil temperature for UHV reactor using Seq2Seq model with convolutional block attention mechanism
Hao Jiang, Hongwei Zhang, Jing Chen, et al.
International Journal of Applied Electromagnetics and Mechanics (2023) Vol. 73, Iss. 4, pp. 283-302
Closed Access | Times Cited: 1
Page 1 - Next Page

Scroll to top