Dingli Yu

2.6k total citations
141 papers, 1.7k citations indexed

About

Dingli Yu is a scholar working on Control and Systems Engineering, Mechanical Engineering and Artificial Intelligence. According to data from OpenAlex, Dingli Yu has authored 141 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 115 papers in Control and Systems Engineering, 37 papers in Mechanical Engineering and 30 papers in Artificial Intelligence. Recurrent topics in Dingli Yu's work include Fault Detection and Control Systems (77 papers), Advanced Control Systems Optimization (54 papers) and Neural Networks and Applications (25 papers). Dingli Yu is often cited by papers focused on Fault Detection and Control Systems (77 papers), Advanced Control Systems Optimization (54 papers) and Neural Networks and Applications (25 papers). Dingli Yu collaborates with scholars based in United Kingdom, China and United States. Dingli Yu's co-authors include J.B. Gomm, D.N. Shields, Yujia Zhai, David Williams, Shuangxin Wang, Yantao Tian, Shiwei Wang, S. Daley, Mahanijah Md Kamal and Qian Zhang and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Information Theory and IEEE Transactions on Industrial Electronics.

In The Last Decade

Dingli Yu

129 papers receiving 1.6k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Dingli Yu United Kingdom	22	1.1k	372	305	227	219	141	1.7k
Erik Frisk Sweden	26	1.6k 1.5×	296 0.8×	287 0.9×	102 0.4×	489 2.2×	157	2.2k
Simone Formentin Italy	24	1.5k 1.4×	131 0.4×	388 1.3×	56 0.2×	540 2.5×	216	2.2k
Wilson Wang Canada	25	1.0k 0.9×	231 0.6×	575 1.9×	279 1.2×	492 2.2×	89	2.0k
Jan Åslund Sweden	18	905 0.8×	118 0.3×	161 0.5×	172 0.8×	919 4.2×	71	1.5k
Rolf Isermann Germany	8	927 0.9×	176 0.5×	376 1.2×	40 0.2×	148 0.7×	52	1.2k
Stefan Jakubek Austria	24	773 0.7×	178 0.5×	299 1.0×	65 0.3×	643 2.9×	180	1.8k
M. Martínez Spain	20	658 0.6×	236 0.6×	146 0.5×	45 0.2×	56 0.3×	90	1.4k
A. Rachid France	17	692 0.6×	85 0.2×	192 0.6×	73 0.3×	229 1.0×	127	1.2k
M. F. Rahmat Malaysia	22	1.1k 1.0×	141 0.4×	838 2.7×	41 0.2×	577 2.6×	178	2.1k

Countries citing papers authored by Dingli Yu

Since Specialization

Citations

This map shows the geographic impact of Dingli Yu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dingli Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dingli Yu more than expected).

Fields of papers citing papers by Dingli Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dingli Yu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dingli Yu. The network helps show where Dingli Yu may publish in the future.

Co-authorship network of co-authors of Dingli Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Dingli Yu. A scholar is included among the top collaborators of Dingli Yu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dingli Yu. Dingli Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Zhu, Qian, Qian Kang, Tao Xu, Dingli Yu, & Zhen Wang. (2025). Deterministic Convergence Analysis for GRU Networks via Smoothing Regularization. Computers, materials & continua/Computers, materials & continua (Print). 83(2). 1855–1879.

Wang, Shuangxin, et al.. (2025). Optimizing wind turbine blade pitch control via input output differential model free adaptive control. Scientific Reports. 15(1). 6325–6325. 1 indexed citations

Yu, Dingli, et al.. (2025). Fault Diagnosis for Electric Vehicle Battery Pack Interconnection System Using Real-World Driving Data. IEEE Transactions on Industrial Electronics. 72(8). 8583–8591.

Wang, Shuangxin, et al.. (2024). Augmenting the diversity of imbalanced datasets via multi-vector stochastic exploration oversampling. Neurocomputing. 583. 127600–127600. 5 indexed citations

Wang, Shuangxin, et al.. (2024). Handling data heterogeneity for wind turbine fault diagnosis via dynamic ensemble multilevel interactive learning. Engineering Applications of Artificial Intelligence. 141. 109716–109716. 1 indexed citations

Ma, Feng‐Yun, et al.. (2023). The diverse effects of cisplatin on tumor microenvironment: Insights and challenges for the delivery of cisplatin by nanoparticles. Environmental Research. 240(Pt 1). 117362–117362. 10 indexed citations

Zhang, Qian, et al.. (2021). A virtual force interaction scheme for multi-robot environment monitoring. Robotics and Autonomous Systems. 149. 103967–103967. 9 indexed citations

Hu, Wei, Zhiyuan Li, & Dingli Yu. (2019). Understanding Generalization of Deep Neural Networks Trained with Noisy Labels.. arXiv (Cornell University). 2 indexed citations

Zhang, Qian, Sarah K. Spurgeon, Li Xu, & Dingli Yu. (2018). Computational Intelligence in Data-Driven Modelling and Its Engineering Applications. Mathematical Problems in Engineering. 2018. 1–2. 3 indexed citations

10.

Gomm, J.B., et al.. (2017). An improved search space resizing method for model identification by standard genetic algorithm. Systems Science & Control Engineering. 5(1). 117–128. 4 indexed citations

11.

Kamal, Mahanijah Md, et al.. (2013). Fault detection and isolation for PEM fuel cell stack with independent RBF model. Engineering Applications of Artificial Intelligence. 28. 52–63. 39 indexed citations

12.

Yu, Dingli, et al.. (2013). Fault detection and isolation based on feedforward-feedback control for oxygen excess of fuel cell stack. 1–5. 2 indexed citations

13.

Zhai, Yujia, et al.. (2010). Robust air/fuel ratio control with adaptive DRNN model and AD tuning. Engineering Applications of Artificial Intelligence. 23(2). 283–289. 25 indexed citations

14.

Yu, Dingli, et al.. (2007). ADAPTIVE FDI FOR AUTOMOTIVE ENGINE AIR PATH AND ROBUSTNESS ASSESSMENT UNDER CLOSED-LOOP CONTROL. International Journal of Automotive Technology. 8(5). 637–650. 1 indexed citations

15.

Yu, Dingli, et al.. (2007). Multi-rate model predictive control of a chemical reactor based on three neural models. Biochemical Engineering Journal. 37(1). 86–97. 6 indexed citations

16.

Yu, Dingli, et al.. (2007). Adaptive RBF network for parameter estimation and stable air–fuel ratio control. Neural Networks. 21(1). 102–112. 43 indexed citations

17.

Yu, Dingli, et al.. (2006). On-board monitoring and diagnosis for spark ignition engine air path via adaptive neural networks. Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering. 220(11). 1641–1655. 10 indexed citations

18.

Yu, Dingli, et al.. (2004). Neural network model adaptation and its application to process control. Advanced Engineering Informatics. 18(1). 1–8. 7 indexed citations

19.

Yu, Dingli, et al.. (2004). Adaptive neural model-based fault tolerant control for multi-variable processes. Engineering Applications of Artificial Intelligence. 18(4). 393–411. 26 indexed citations

20.

Wang, J., H. S. Sii, Jianbo Yang, et al.. (2004). Use of Advances in Technology for Maritime Risk Assessment. Risk Analysis. 24(4). 1041–1063. 58 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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