Zhenyu Meng

2.5k total citations
67 papers, 1.8k citations indexed

About

Zhenyu Meng is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Zhenyu Meng has authored 67 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Artificial Intelligence, 42 papers in Computational Theory and Mathematics and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Zhenyu Meng's work include Metaheuristic Optimization Algorithms Research (54 papers), Evolutionary Algorithms and Applications (43 papers) and Advanced Multi-Objective Optimization Algorithms (42 papers). Zhenyu Meng is often cited by papers focused on Metaheuristic Optimization Algorithms Research (54 papers), Evolutionary Algorithms and Applications (43 papers) and Advanced Multi-Objective Optimization Algorithms (42 papers). Zhenyu Meng collaborates with scholars based in China, Taiwan and Australia. Zhenyu Meng's co-authors include Jeng‐Shyang Pan, Cheng Yang, Kuo-Kun Tseng, Huarong Xu, Lingping Kong, Guojun Mao, Yan Liang, Xiaoqing Li, Quanbin Zhang and Shu‐Chuan Chu and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

In The Last Decade

Zhenyu Meng

65 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhenyu Meng China 22 1.4k 880 171 137 111 67 1.8k
Noor H. Awad Jordan 18 1.2k 0.8× 746 0.8× 249 1.5× 178 1.3× 114 1.0× 31 1.6k
Mirjam Sepesy Maučec Slovenia 18 1.6k 1.2× 1.1k 1.2× 126 0.7× 149 1.1× 113 1.0× 54 2.0k
Anas A. Hadi Egypt 12 990 0.7× 558 0.6× 157 0.9× 120 0.9× 143 1.3× 20 1.4k
Ryoji Tanabe Japan 11 2.1k 1.5× 1.6k 1.8× 257 1.5× 221 1.6× 153 1.4× 24 2.7k
Changhe Li China 19 1.3k 0.9× 984 1.1× 165 1.0× 194 1.4× 133 1.2× 67 1.8k
Tong Han China 19 794 0.6× 382 0.4× 297 1.7× 197 1.4× 205 1.8× 50 1.5k
Mohammed Jameel Yemen 9 714 0.5× 351 0.4× 227 1.3× 201 1.5× 183 1.6× 19 1.3k
Abhishek Kumar India 18 897 0.6× 668 0.8× 279 1.6× 286 2.1× 116 1.0× 63 1.4k
Subhodip Biswas India 16 718 0.5× 556 0.6× 151 0.9× 101 0.7× 70 0.6× 30 997
Ali Khater Mohamed Egypt 9 690 0.5× 371 0.4× 135 0.8× 99 0.7× 98 0.9× 12 940

Countries citing papers authored by Zhenyu Meng

Since Specialization
Citations

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

Fields of papers citing papers by Zhenyu Meng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhenyu Meng

This figure shows the co-authorship network connecting the top 25 collaborators of Zhenyu Meng. A scholar is included among the top collaborators of Zhenyu Meng 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 Zhenyu Meng. Zhenyu Meng 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.
Meng, Zhenyu, et al.. (2025). Surrogate-assisted differential evolution: A survey. Swarm and Evolutionary Computation. 94. 101879–101879. 3 indexed citations
2.
Meng, Zhenyu, et al.. (2025). A survey on expensive optimization problems using differential evolution. Applied Soft Computing. 170. 112727–112727.
3.
Dou, Hao, et al.. (2025). Graph anomaly detection based on hybrid node representation learning. Neural Networks. 185. 107169–107169. 2 indexed citations
4.
Wang, Ruo-Bin, Lin Xu, Shu‐Chuan Chu, et al.. (2025). The Animated Oat Optimization Algorithm: A nature-inspired metaheuristic for engineering optimization and a case study on Wireless Sensor Networks. Knowledge-Based Systems. 318. 113589–113589. 15 indexed citations
5.
Meng, Zhenyu, et al.. (2024). Surrogate-Assisted Differential Evolution with multiple sampling mechanisms for high-dimensional expensive problems. Information Sciences. 687. 121408–121408. 4 indexed citations
6.
Meng, Zhenyu, et al.. (2024). Surrogate-assisted evolutionary framework with an ensemble of teaching-learning and differential evolution for expensive optimization. Information Sciences. 680. 121137–121137. 4 indexed citations
7.
Meng, Zhenyu, et al.. (2024). Surrogate-assisted fully-informed particle swarm optimization for high-dimensional expensive optimization. Applied Soft Computing. 167. 112464–112464. 7 indexed citations
8.
Zhang, Quanbin & Zhenyu Meng. (2024). HAPI-DE: Differential evolution with hierarchical archive based mutation strategy and promising information. Swarm and Evolutionary Computation. 91. 101705–101705. 7 indexed citations
9.
Meng, Zhenyu, et al.. (2024). Hybrid-attention mechanism based heterogeneous graph representation learning. Expert Systems with Applications. 250. 123963–123963. 4 indexed citations
10.
Meng, Zhenyu, et al.. (2024). Elite-guided Resampling and Multi-mutation based Differential Evolution with exponential crossover for numerical optimization. Expert Systems with Applications. 258. 125159–125159. 3 indexed citations
11.
Meng, Zhenyu, et al.. (2024). An adaptative differential evolution with enhanced diversity and restart mechanism. Expert Systems with Applications. 249. 123634–123634. 10 indexed citations
12.
Meng, Zhenyu, et al.. (2024). A Surrogate-Assisted Differential Evolution with fitness-independent parameter adaptation for high-dimensional expensive optimization. Information Sciences. 662. 120246–120246. 19 indexed citations
13.
Zhou, Wentao & Zhenyu Meng. (2024). An adaptive differential evolution with dynamic perturbation and dimensional bidirectional crossover mechanism for diversity enhancement. Engineering Applications of Artificial Intelligence. 141. 109750–109750. 7 indexed citations
14.
Meng, Zhenyu, et al.. (2023). QUATRE-EMS: QUATRE algorithm with novel adaptation of evolution matrix and selection operation for numerical optimization. Information Sciences. 651. 119714–119714. 20 indexed citations
15.
Meng, Zhenyu. (2023). Dimension improvements based adaptation of control parameters in Differential Evolution: A fitness-value-independent approach. Expert Systems with Applications. 223. 119848–119848. 47 indexed citations
16.
Meng, Zhenyu, et al.. (2023). Differential Evolution with exponential crossover can be also competitive on numerical optimization. Applied Soft Computing. 146. 110750–110750. 49 indexed citations
17.
Meng, Zhenyu, et al.. (2023). Differential Evolution with perturbation mechanism and covariance matrix based stagnation indicator for numerical optimization. Swarm and Evolutionary Computation. 84. 101447–101447. 24 indexed citations
18.
Meng, Zhenyu, et al.. (2023). FD-DE: Differential Evolution with fitness deviation based adaptation in parameter control. ISA Transactions. 139. 272–290. 18 indexed citations
19.
Chu, Shu‐Chuan, et al.. (2020). Internal search of the evolution matrix in QUasi-Affine TRansformation Evolution (QUATRE) algorithm. Journal of Intelligent & Fuzzy Systems. 38(5). 5673–5684. 5 indexed citations
20.
Pan, Jeng‐Shyang, Zhenyu Meng, Shaoquan Ni, & Shu‐Chuan Chu. (2019). A novel Differential Evolution approach to scheduling the freight trains in intervals of passenger trains. 3777–3783. 4 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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