M.Z. Liu

414 total citations
21 papers, 352 citations indexed

About

M.Z. Liu is a scholar working on Numerical Analysis, Applied Mathematics and Modeling and Simulation. According to data from OpenAlex, M.Z. Liu has authored 21 papers receiving a total of 352 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Numerical Analysis, 7 papers in Applied Mathematics and 6 papers in Modeling and Simulation. Recurrent topics in M.Z. Liu's work include Differential Equations and Numerical Methods (14 papers), Numerical methods for differential equations (13 papers) and Nonlinear Differential Equations Analysis (6 papers). M.Z. Liu is often cited by papers focused on Differential Equations and Numerical Methods (14 papers), Numerical methods for differential equations (13 papers) and Nonlinear Differential Equations Analysis (6 papers). M.Z. Liu collaborates with scholars based in China and Spain. M.Z. Liu's co-authors include Minghui Song, Zhanwen Yang, D. Li, Jingjun Zhao, Yang Xu, Qingyong Zhu, Hui Liang, X. Liu, Yulan Lu and Juan J. Nieto and has published in prestigious journals such as Applied Mathematics and Computation, IEEE Sensors Journal and Computers & Mathematics with Applications.

In The Last Decade

M.Z. Liu

19 papers receiving 340 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M.Z. Liu China	10	281	156	122	56	39	21	352
Rob De Staelen Belgium	11	233 0.8×	295 1.9×	86 0.7×	33 0.6×	30 0.8×	29	406
Ali Demir Türkiye	11	194 0.7×	277 1.8×	150 1.2×	50 0.9×	29 0.7×	68	397
Toshiyuki Koto Japan	11	283 1.0×	86 0.6×	34 0.3×	114 2.0×	35 0.9×	17	373
Jinghua Chen China	6	122 0.4×	236 1.5×	145 1.2×	15 0.3×	32 0.8×	12	319
M. Yousuf Saudi Arabia	13	214 0.8×	129 0.8×	28 0.2×	29 0.5×	41 1.1×	36	431
Azmat Ullah Khan Niazi Pakistan	12	72 0.3×	281 1.8×	247 2.0×	23 0.4×	102 2.6×	68	401
Daniel F. Shea United States	14	139 0.5×	81 0.5×	351 2.9×	138 2.5×	88 2.3×	29	571
M. Kwapisz Poland	11	263 0.9×	51 0.3×	190 1.6×	117 2.1×	45 1.2×	58	402
D. Bahuguna India	16	253 0.9×	323 2.1×	511 4.2×	127 2.3×	205 5.3×	62	635
Jugal Mohapatra India	16	739 2.6×	283 1.8×	189 1.5×	264 4.7×	20 0.5×	97	843

Countries citing papers authored by M.Z. Liu

Since Specialization

Citations

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

Fields of papers citing papers by M.Z. Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.Z. Liu. 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 M.Z. Liu. The network helps show where M.Z. Liu may publish in the future.

Co-authorship network of co-authors of M.Z. Liu

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

All Works

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20 of 20 papers shown

Liu, M.Z., et al.. (2025). GEO Spatial Correlation SAR Imaging Framework Using MBO2D-SC Algorithm for Sea Surface Wave Imaging Under Prolonged Synthetic Aperture Time. IEEE Sensors Journal. 25(13). 25168–25184.

Yu, Yue & M.Z. Liu. (2024). The consensus among distributed information processing nodes in a limited and uncertain communication setting. Digital Signal Processing. 147. 104398–104398.

Song, Minghui, Yulan Lu, & M.Z. Liu. (2017). Convergence of the Tamed Euler Method for Stochastic Differential Equations with Piecewise Continuous Arguments Under Non-global Lipschitz Continuous Coefficients. Numerical Functional Analysis and Optimization. 39(5). 517–536. 5 indexed citations

Song, Minghui, et al.. (2017). Strong convergence of the truncated Euler–Maruyama method for stochastic functional differential equations. International Journal of Computer Mathematics. 95(12). 2363–2387. 9 indexed citations

Song, Minghui, et al.. (2016). Convergence and stability of impulsive stochastic differential equations. International Journal of Computer Mathematics. 94(9). 1738–1746. 6 indexed citations

Liu, M.Z., et al.. (2013). New Iterative Method Based on Laplace Decomposition Algorithm. Journal of Applied Mathematics. 2013. 1–7. 5 indexed citations

Liu, X., Minghui Song, & M.Z. Liu. (2012). Linear Multistep Methods for Impulsive Differential Equations. Discrete Dynamics in Nature and Society. 2012(1). 10 indexed citations

Song, Minghui & M.Z. Liu. (2012). Stability of Analytic and Numerical Solutions for Differential Equations with Piecewise Continuous Arguments. Abstract and Applied Analysis. 2012(1). 4 indexed citations

Liang, Hui, Minghui Song, & M.Z. Liu. (2010). Stability of the analytic and numerical solutions for impulsive differential equations. Applied Numerical Mathematics. 61(11). 1103–1113. 17 indexed citations

10.

Yang, Zhanwen, M.Z. Liu, & Juan J. Nieto. (2009). Runge–Kutta methods for first-order periodic boundary value differential equations with piecewise constant arguments. Journal of Computational and Applied Mathematics. 233(4). 990–1004. 5 indexed citations

11.

Song, Minghui, et al.. (2009). Exponential stability of Euler–Maruyama solutions for impulsive stochastic differential equations with delay. Applied Mathematics and Computation. 215(9). 3425–3432. 8 indexed citations

12.

Liu, M.Z., et al.. (2007). Numerical methods for impulsive differential equation. Mathematical and Computer Modelling. 48(1-2). 46–55. 36 indexed citations

13.

Yang, Zhanwen, et al.. (2007). Stability of Runge–Kutta methods for the alternately advanced and retarded differential equations with piecewise continuous arguments. Computers & Mathematics with Applications. 54(3). 326–335. 8 indexed citations

14.

Zhao, Jingjun, et al.. (2006). Stability of a class of Runge–Kutta methods for a family of pantograph equations of neutral type. Applied Mathematics and Computation. 181(2). 1170–1181. 19 indexed citations

15.

Song, Minghui, Zhanwen Yang, & M.Z. Liu. (2005). Stability of θ-methods for advanced differential equations with piecewise continuous arguments. Computers & Mathematics with Applications. 49(9-10). 1295–1301. 48 indexed citations

16.

Liu, M.Z., et al.. (2005). Asymptotical Stability of Numerical Methods with Constant Stepsize for Pantograph Equations. BIT Numerical Mathematics. 45(4). 743–759. 29 indexed citations

17.

Liu, M.Z., Minghui Song, & Zhanwen Yang. (2004). Stability of Runge–Kutta methods in the numerical solution of equation u′(t)=au(t)+a0u([t]). Journal of Computational and Applied Mathematics. 166(2). 361–370. 41 indexed citations

18.

Zhao, Jingjun, Yang Xu, & M.Z. Liu. (2004). Stability analysis of numerical methods for linear neutral Volterra delay-integro-differential system. Applied Mathematics and Computation. 167(2). 1062–1079. 31 indexed citations

19.

Zhao, Jingjun, et al.. (2004). Stability of the Rosenbrock methods for the neutral delay differential-algebraic equations. Applied Mathematics and Computation. 168(2). 1128–1144. 9 indexed citations

20.

Li, D. & M.Z. Liu. (2004). Runge–Kutta methods for the multi-pantograph delay equation. Applied Mathematics and Computation. 163(1). 383–395. 52 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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