Hua‐Liang Wei

5.7k total citations
161 papers, 4.1k citations indexed

About

Hua‐Liang Wei is a scholar working on Control and Systems Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Hua‐Liang Wei has authored 161 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Control and Systems Engineering, 49 papers in Artificial Intelligence and 24 papers in Computer Vision and Pattern Recognition. Recurrent topics in Hua‐Liang Wei's work include Control Systems and Identification (38 papers), Fault Detection and Control Systems (32 papers) and Neural Networks and Applications (26 papers). Hua‐Liang Wei is often cited by papers focused on Control Systems and Identification (38 papers), Fault Detection and Control Systems (32 papers) and Neural Networks and Applications (26 papers). Hua‐Liang Wei collaborates with scholars based in United Kingdom, China and United States. Hua‐Liang Wei's co-authors include S.A. Billings, S.A. Billings, Zhaohua Liu, М. А. Балихин, Xiaohua Li, Lei Chen, Yifan Zhao, Ptolemaios G. Sarrigiannis, Richard Boynton and Biliang Lu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Hua‐Liang Wei

153 papers receiving 4.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hua‐Liang Wei United Kingdom 37 1.5k 959 583 530 430 161 4.1k
Babak Nadjar Araabi Iran 33 764 0.5× 1.1k 1.2× 580 1.0× 442 0.8× 120 0.3× 276 3.8k
Michael J. Korenberg Canada 28 1.4k 0.9× 985 1.0× 735 1.3× 431 0.8× 54 0.1× 140 4.0k
S.A. Billings United Kingdom 42 4.4k 2.9× 2.5k 2.6× 501 0.9× 291 0.5× 318 0.7× 178 7.6k
Paulo Gonçalvès France 16 1.6k 1.1× 281 0.3× 494 0.8× 408 0.8× 68 0.2× 44 4.1k
Gabriel Rilling France 14 2.1k 1.4× 283 0.3× 600 1.0× 467 0.9× 74 0.2× 35 4.5k
Gérard Dreyfus France 31 508 0.3× 1.5k 1.5× 954 1.6× 688 1.3× 64 0.1× 144 4.2k
Türker İnce Türkiye 30 1.7k 1.1× 1.2k 1.3× 789 1.4× 1.6k 3.0× 40 0.1× 84 7.4k
P. A. Estévez Chile 28 243 0.2× 1.4k 1.4× 358 0.6× 295 0.6× 187 0.4× 131 3.5k
Marı́a E. Torres Argentina 18 1.2k 0.8× 421 0.4× 854 1.5× 241 0.5× 31 0.1× 56 3.8k
Frank Kirchner Germany 33 887 0.6× 314 0.3× 200 0.3× 407 0.8× 122 0.3× 266 4.5k

Countries citing papers authored by Hua‐Liang Wei

Since Specialization
Citations

This map shows the geographic impact of Hua‐Liang Wei'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 Hua‐Liang Wei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hua‐Liang Wei more than expected).

Fields of papers citing papers by Hua‐Liang Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hua‐Liang Wei. 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 Hua‐Liang Wei. The network helps show where Hua‐Liang Wei may publish in the future.

Co-authorship network of co-authors of Hua‐Liang Wei

This figure shows the co-authorship network connecting the top 25 collaborators of Hua‐Liang Wei. A scholar is included among the top collaborators of Hua‐Liang Wei 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 Hua‐Liang Wei. Hua‐Liang Wei is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Dong, Yuning, et al.. (2025). New Class Detection in Network Traffic Classification Using Confidence Information Embedded Cascade Structure. IEEE Transactions on Network Science and Engineering. 12(3). 1692–1706.
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Dong, Yuning, et al.. (2023). Online Classification of Network Traffic Based on Granular Computing. IEEE Transactions on Systems Man and Cybernetics Systems. 53(8). 5199–5211. 6 indexed citations
6.
Lu, Biliang, et al.. (2023). A novel sample selection approach based universal unsupervised domain adaptation for fault diagnosis of rotating machinery. Reliability Engineering & System Safety. 240. 109618–109618. 21 indexed citations
7.
Dong, Yuning, et al.. (2022). Multimedia Traffic Classification for Imbalanced Environment. IEEE Transactions on Network Science and Engineering. 9(3). 1838–1852. 4 indexed citations
8.
Hall, Richard J., Hua‐Liang Wei, & Edward Hanna. (2019). Complex systems modelling for statistical forecasting of winter North Atlantic atmospheric variability: A new approach to North Atlantic seasonal forecasting. Quarterly Journal of the Royal Meteorological Society. 145(723). 2568–2585. 11 indexed citations
9.
Oko, Eni, et al.. (2018). Non-linear system identification of solvent-based post-combustion CO2 capture process. Fuel. 239. 1213–1223. 20 indexed citations
10.
Zuo, Cili, et al.. (2017). Stochastic Fractal Based Multiobjective Fruit Fly Optimization. SHILAP Revista de lepidopterología. 9 indexed citations
11.
Li, Yang, Weigang Cui, Yuzhu Guo, et al.. (2017). Time-Varying System Identification Using an Ultra-Orthogonal Forward Regression and Multiwavelet Basis Functions With Applications to EEG. IEEE Transactions on Neural Networks and Learning Systems. 29(7). 1–13. 40 indexed citations
12.
He, Fei, S.A. Billings, Hua‐Liang Wei, & Ptolemaios G. Sarrigiannis. (2014). A nonlinear causality measure in the frequency domain: Nonlinear partial directed coherence with applications to EEG. Journal of Neuroscience Methods. 225. 71–80. 35 indexed citations
13.
He, Fei, Hua‐Liang Wei, & S.A. Billings. (2013). Identification and frequency domain analysis of non-stationary and nonlinear systems using time-varying NARMAX models. International Journal of Systems Science. 46(11). 2087–2100. 21 indexed citations
14.
He, Fei, S.A. Billings, Hua‐Liang Wei, Ptolemaios G. Sarrigiannis, & Yifan Zhao. (2013). Spectral Analysis for Nonstationary and Nonlinear Systems: A Discrete-Time-Model-Based Approach. IEEE Transactions on Biomedical Engineering. 60(8). 2233–2241. 16 indexed citations
15.
Li, Yang, Hua‐Liang Wei, S.A. Billings, & Xiaofeng Liao. (2012). Time-varying linear and nonlinear parametric model for Granger causality analysis. Physical Review E. 85(4). 41906–41906. 29 indexed citations
16.
Li, Yang, Hua‐Liang Wei, S.A. Billings, & Ptolemaios G. Sarrigiannis. (2010). Time-varying model identification for time–frequency feature extraction from EEG data. Journal of Neuroscience Methods. 196(1). 151–158. 35 indexed citations
17.
Billings, S.A. & Hua‐Liang Wei. (2008). An adaptive orthogonal search algorithm for model subset selection and non-linear system identification. International Journal of Control. 81(5). 714–724. 77 indexed citations
18.
Wei, Hua‐Liang & S.A. Billings. (2006). Long term prediction of non-linear time series using multiresolution wavelet models. International Journal of Control. 79(6). 569–580. 19 indexed citations
19.
Billings, S.A. & Hua‐Liang Wei. (2005). The wavelet-NARMAX representation: A hybrid model structure combining polynomial models with multiresolution wavelet decompositions. International Journal of Systems Science. 36(3). 137–152. 59 indexed citations
20.
Wei, Hua‐Liang & S.A. Billings. (2004). Identification and reconstruction of chaotic systems using multiresolution wavelet decompositions. International Journal of Systems Science. 35(9). 511–526. 18 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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