Yu‐Ming Chu

34.7k total citations · 22 hit papers
935 papers, 28.7k citations indexed

About

Yu‐Ming Chu is a scholar working on Applied Mathematics, Geometry and Topology and Biomedical Engineering. According to data from OpenAlex, Yu‐Ming Chu has authored 935 papers receiving a total of 28.7k indexed citations (citations by other indexed papers that have themselves been cited), including 461 papers in Applied Mathematics, 209 papers in Geometry and Topology and 197 papers in Biomedical Engineering. Recurrent topics in Yu‐Ming Chu's work include Mathematical Inequalities and Applications (398 papers), Functional Equations Stability Results (231 papers) and Nanofluid Flow and Heat Transfer (187 papers). Yu‐Ming Chu is often cited by papers focused on Mathematical Inequalities and Applications (398 papers), Functional Equations Stability Results (231 papers) and Nanofluid Flow and Heat Transfer (187 papers). Yu‐Ming Chu collaborates with scholars based in China, Pakistan and Saudi Arabia. Yu‐Ming Chu's co-authors include Tie‐Hong Zhao, Miao-Kun Wang, M. Ijaz Khan, Saima Rashid, Muhammad Adil Khan, Seifedine Kadry, Zhen-Hang Yang, Shengyuan Xu, Wei-Mao Qian and Sami Ullah Khan and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Yu‐Ming Chu

918 papers receiving 26.8k citations

Hit Papers

Artificial neural network... 2018 2026 2020 2023 2021 2021 2022 2021 2021 100 200 300 400

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Yu‐Ming Chu 10.8k 8.3k 7.6k 5.5k 4.7k 935 28.7k
Kottakkaran Sooppy Nisar 4.4k 0.4× 9.0k 1.1× 7.3k 1.0× 6.0k 1.1× 8.2k 1.7× 1.1k 21.9k
Poom Kumam 1.4k 0.1× 7.8k 0.9× 6.0k 0.8× 6.4k 1.2× 3.0k 0.6× 1.1k 20.1k
Ji‐Huan He 2.7k 0.2× 10.0k 1.2× 2.4k 0.3× 2.9k 0.5× 32.4k 6.8× 581 46.7k
S. Abbasbandy 2.2k 0.2× 4.3k 0.5× 2.8k 0.4× 3.0k 0.6× 7.4k 1.6× 389 14.6k
Thabet Abdeljawad 9.6k 0.9× 1.2k 0.1× 842 0.1× 761 0.1× 13.4k 2.8× 827 19.4k
YangQuan Chen 2.5k 0.2× 2.2k 0.3× 3.8k 0.5× 766 0.1× 12.0k 2.5× 1.1k 38.5k
Mehdi Dehghan 4.8k 0.4× 1.4k 0.2× 636 0.1× 5.2k 0.9× 15.6k 3.3× 752 29.7k
Shaher Momani 3.6k 0.3× 1.7k 0.2× 839 0.1× 934 0.2× 13.1k 2.8× 421 17.8k
J. A. Tenreiro Machado 3.5k 0.3× 1.6k 0.2× 893 0.1× 590 0.1× 11.9k 2.5× 752 22.5k
Shijun Liao 779 0.1× 9.2k 1.1× 5.2k 0.7× 6.2k 1.1× 9.8k 2.1× 263 19.4k

Countries citing papers authored by Yu‐Ming Chu

Since Specialization
Citations

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

Fields of papers citing papers by Yu‐Ming Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yu‐Ming Chu. 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 Yu‐Ming Chu. The network helps show where Yu‐Ming Chu may publish in the future.

Co-authorship network of co-authors of Yu‐Ming Chu

This figure shows the co-authorship network connecting the top 25 collaborators of Yu‐Ming Chu. A scholar is included among the top collaborators of Yu‐Ming Chu 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 Yu‐Ming Chu. Yu‐Ming Chu 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.
Arockiaraj, Micheal, et al.. (2023). Entropy structural characterization of zeolites BCT and DFT with bond-wise scaled comparison. Scientific Reports. 13(1). 10874–10874. 26 indexed citations
2.
Chu, Yu‐Ming, et al.. (2023). An advanced approach for the electrical responses of discrete fractional-order biophysical neural network models and their dynamical responses. Scientific Reports. 13(1). 18180–18180. 6 indexed citations
3.
Wang, Miao-Kun, et al.. (2023). Sharp exponential type inequalities for the arc lemniscate sine function with applications. Journal of Mathematical Inequalities. 517–530. 1 indexed citations
4.
Chu, Yu‐Ming, et al.. (2023). Fractional quantum analogues of trapezoid like inequalities. Journal of Mathematical Inequalities. 31–47. 1 indexed citations
5.
Chu, Yu‐Ming, et al.. (2023). New Configurations of the Fuzzy Fractional Differential Boussinesq Model with Application in Ocean Engineering and Their Analysis in Statistical Theory. Computer Modeling in Engineering & Sciences. 137(2). 1573–1611. 3 indexed citations
6.
Chu, Yu‐Ming, M.S. Al-Buriahi, Aamir Khan, et al.. (2023). Significance of generalized Fourier and Fick’s law and stagnation point flow for magnetized viscoelastic liquids. Materials Science and Engineering B. 296. 116602–116602. 2 indexed citations
7.
Yao, Qijia, et al.. (2023). NEURAL LEARNING CONTROL METHODOLOGY FOR PREDEFINED-TIME SYNCHRONIZATION OF UNKNOWN CHAOTIC SYSTEMS. Fractals. 31(6). 1 indexed citations
9.
Algehyne, Ebrahem A., Tareq Saeed, Muhammad Ibrahim, Abdallah S. Berrouk, & Yu‐Ming Chu. (2021). Investigation of dissimilar laser welding of stainless steel 304 and copper using the artificial neural network model. Journal of Laser Applications. 33(2). 10 indexed citations
11.
Chu, Yu‐Ming, Mostafa M. A. Khater, & Y. S. Hamed. (2021). Diverse novel analytical and semi-analytical wave solutions of the generalized (2+1)-dimensional shallow water waves model. AIP Advances. 11(1). 62 indexed citations
12.
Abbas, Syed Zaheer, Shahid Farooq, Yu‐Ming Chu, et al.. (2021). Numerical Study of Nanofluid Transport Subjected to the Collective Approach of Generalized Slip Condition and Radiative Phenomenon. Arabian Journal for Science and Engineering. 46(6). 6049–6059. 7 indexed citations
13.
Ashraf, Muhammad Usman, et al.. (2020). Computational Analysis of the Effect of Nano Particle Material Motion on Mixed Convection Flow in the Presence of Heat Generation and Absorption. Computers, materials & continua/Computers, materials & continua (Print). 65(2). 1809–1823. 26 indexed citations
14.
Abbasi, Adnan, Umar Khan, Naveed Ahmed, et al.. (2020). Impacts of Freezing Temperature Based Thermal Conductivity on the Heat Transfer Gradient in Nanofluids: Applications for a Curved Riga Surface. Molecules. 25(9). 2152–2152. 30 indexed citations
15.
Khater, Mostafa M. A., Yu‐Ming Chu, Raghda A. M. Attia, & Dianchen Lu. (2020). On the Analytical and Numerical Solutions in the Quantum Magnetoplasmas: The Atangana Conformable Derivative (1+3)-ZK Equation with Power-Law Nonlinearity. Advances in Mathematical Physics. 2020. 1–10. 10 indexed citations
16.
Jahanshahi, Hadi, et al.. (2020). Optimal Control of Time-Delay Fractional Equations via a Joint Application of Radial Basis Functions and Collocation Method. Entropy. 22(11). 1213–1213. 58 indexed citations
18.
Tan, Fei, Lili Zhou, Junwei Lu, Yu‐Ming Chu, & Yongmin Li. (2020). Fixed‐time outer synchronization under double‐layered multiplex networks with hybrid links and time‐varying delays via delayed feedback control. Asian Journal of Control. 24(1). 137–148. 12 indexed citations
19.
Cui, Lei, et al.. (2020). Adaptive Prescribed Performance Output Regulation of Nonlinear Systems with Nonlinear Exosystems. International Journal of Control Automation and Systems. 18(8). 1946–1955. 13 indexed citations
20.
Song, Ying-Qing, et al.. (2018). Integral Inequalities Involving Strongly Convex Functions. Journal of Function Spaces. 2018. 1–8. 48 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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