S. Shao

622 total citations
24 papers, 489 citations indexed

About

S. Shao is a scholar working on Control and Systems Engineering, Artificial Intelligence and Numerical Analysis. According to data from OpenAlex, S. Shao has authored 24 papers receiving a total of 489 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Control and Systems Engineering, 7 papers in Artificial Intelligence and 6 papers in Numerical Analysis. Recurrent topics in S. Shao's work include Adaptive Control of Nonlinear Systems (7 papers), Differential Equations and Numerical Methods (6 papers) and Neural Networks and Applications (6 papers). S. Shao is often cited by papers focused on Adaptive Control of Nonlinear Systems (7 papers), Differential Equations and Numerical Methods (6 papers) and Neural Networks and Applications (6 papers). S. Shao collaborates with scholars based in United States, China and Hong Kong. S. Shao's co-authors include Zhiqiang Gao, Rafał Madoński, Jun Yang, Momir Stanković, Mario Ramírez‐Neria, Shihua Li, Jun Yang, Ka Fai Cedric Yiu, Leong Kwan Li and Krzysztof Łakomy and has published in prestigious journals such as Mechanical Systems and Signal Processing, Applied Soft Computing and Journal of Mathematical Analysis and Applications.

In The Last Decade

S. Shao

23 papers receiving 473 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
S. Shao United States	10	396	113	92	33	32	24	489
E. Ostertag France	12	522 1.3×	61 0.5×	122 1.3×	37 1.1×	27 0.8×	29	580
Francesco Alessandro Cuzzola Italy	14	754 1.9×	72 0.6×	117 1.3×	27 0.8×	24 0.8×	32	870
K. Uchida Japan	11	321 0.8×	96 0.8×	62 0.7×	13 0.4×	38 1.2×	31	398
Tito L.M. Santos Brazil	16	559 1.4×	57 0.5×	67 0.7×	27 0.8×	31 1.0×	79	694
John Cortés‐Romero Colombia	17	593 1.5×	246 2.2×	122 1.3×	60 1.8×	49 1.5×	67	747
Sudhir Agashe India	8	537 1.4×	182 1.6×	75 0.8×	50 1.5×	32 1.0×	33	689
Miroslav R. Mataušek Serbia	15	951 2.4×	98 0.9×	61 0.7×	36 1.1×	11 0.3×	35	1.1k
Nasser Sadati Iran	8	702 1.8×	239 2.1×	59 0.6×	33 1.0×	59 1.8×	20	802
Ali J. Koshkouei United Kingdom	16	656 1.7×	81 0.7×	98 1.1×	16 0.5×	71 2.2×	44	756
M. Zhuang United Kingdom	9	634 1.6×	75 0.7×	56 0.6×	20 0.6×	21 0.7×	11	714

Countries citing papers authored by S. Shao

Since Specialization

Citations

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

Fields of papers citing papers by S. Shao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. Shao. 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 S. Shao. The network helps show where S. Shao may publish in the future.

Co-authorship network of co-authors of S. Shao

This figure shows the co-authorship network connecting the top 25 collaborators of S. Shao. A scholar is included among the top collaborators of S. Shao 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 S. Shao. S. Shao 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

Ramírez‐Neria, Mario, Rafał Madoński, S. Shao, & Zhiqiang Gao. (2020). Robust Tracking in Underactuated Systems Using Flatness-Based ADRC With Cascade Observers. Journal of Dynamic Systems Measurement and Control. 142(9). 25 indexed citations

Madoński, Rafał, Krzysztof Łakomy, Momir Stanković, et al.. (2020). Robust converter-fed motor control based on active rejection of multiple disturbances. Control Engineering Practice. 107. 104696–104696. 29 indexed citations

Madoński, Rafał, Momir Stanković, S. Shao, et al.. (2020). Active disturbance rejection control of torsional plant with unknown frequency harmonic disturbance. Control Engineering Practice. 100. 104413–104413. 41 indexed citations

Madoński, Rafał, et al.. (2020). General ADRC Design for Systems With Periodic Disturbances of Unknown and Varying Frequencies. Journal of Dynamic Systems Measurement and Control. 143(1). 14 indexed citations

Madoński, Rafał, Mario Ramírez‐Neria, Momir Stanković, et al.. (2019). On vibration suppression and trajectory tracking in largely uncertain torsional system: An error-based ADRC approach. Mechanical Systems and Signal Processing. 134. 106300–106300. 54 indexed citations

Shao, S. & Zhiqiang Gao. (2016). On the conditions of exponential stability in active disturbance rejection control based on singular perturbation analysis. International Journal of Control. 90(10). 2085–2097. 82 indexed citations

Shao, S., et al.. (2014). Convergence analysis of the weighted state space search algorithm for recurrent neural networks. Numerical Algebra Control and Optimization. 4(3). 193–207. 1 indexed citations

Li, Leong Kwan, S. Shao, & Ka Fai Cedric Yiu. (2012). A new optimization algorithm for single hidden layer feedforward neural networks. Applied Soft Computing. 13(5). 2857–2862. 18 indexed citations

Shao, S., et al.. (2009). A Stability Study of the Active Disturbance Rejection Control Problem by a Singular Perturbation Approach. Applied mathematical sciences. 3(10). 491–508. 59 indexed citations

10.

Shao, S., et al.. (2008). A State Space Search Algorithm and its Application to Learn the Short-Term Foreign Exchange Rates. Applied mathematical sciences. 2(35). 1705–1728. 3 indexed citations

11.

Shao, S., et al.. (2008). A Neural Network Approach for Global Optimization with Applications. Neural Network World. 3(10). 491–508. 3 indexed citations

12.

Shao, S., et al.. (2007). Dynamic Properties of Recurrent Neural Netowrks and Its Applications. EngagedScholarship @ Cleveland State University (Cleveland State University). 39(4). 545–562. 2 indexed citations

13.

Shao, S.. (2006). Asymptotic analysis and domain decomposition for a singularly perturbed reaction–convection–diffusion system with shock–interior layer interactions. Nonlinear Analysis. 66(2). 271–287. 5 indexed citations

14.

Shao, S., et al.. (2006). A Neural Network Approach for Global Optimization with Applications to Nonlinear Least Square Problems. EngagedScholarship @ Cleveland State University (Cleveland State University). 130–134. 1 indexed citations

15.

Shao, S.. (2003). Asymptotic solutions of diffusion models for risk reserves. International Journal of Mathematics and Mathematical Sciences. 2003(35). 2221–2239.

16.

Shao, S., et al.. (2000). Rates of Convergence of Adaptive Step-Size of Stochastic Approximation Algorithms. Journal of Mathematical Analysis and Applications. 244(2). 333–347. 1 indexed citations

17.

Shao, S. & R.C.Y. Chin. (1996). An asymptotic-numerical method for a time-dependent singularly perturbed system with turning points. Numerical Methods for Partial Differential Equations. 12(4). 441–460. 5 indexed citations

18.

Shao, S.. (1994). Asymptotic Behavior of Solutions of Model Problems for a Coupled System. Journal of Mathematical Analysis and Applications. 181(1). 150–170. 2 indexed citations

19.

Shao, S.. (1994). Boundary and interior layer behavior in a time-dependent singularly perturbed system. Nonlinear Analysis. 22(9). 1105–1119. 3 indexed citations

20.

Harris, William A. & S. Shao. (1991). Refined approximations of the solutions of a coupled system with turning points. Journal of Differential Equations. 92(1). 125–144. 3 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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