Mei-qing An

548 total citations
13 papers, 442 citations indexed

About

Mei-qing An is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Industrial and Manufacturing Engineering. According to data from OpenAlex, Mei-qing An has authored 13 papers receiving a total of 442 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Industrial and Manufacturing Engineering. Recurrent topics in Mei-qing An's work include Metaheuristic Optimization Algorithms Research (13 papers), Robotic Path Planning Algorithms (6 papers) and Advanced Multi-Objective Optimization Algorithms (4 papers). Mei-qing An is often cited by papers focused on Metaheuristic Optimization Algorithms Research (13 papers), Robotic Path Planning Algorithms (6 papers) and Advanced Multi-Objective Optimization Algorithms (4 papers). Mei-qing An collaborates with scholars based in China. Mei-qing An's co-authors include Wanli Xiang, Yinzhen Li, Ruichun He, Xuelei Meng, Shoufeng Ma, Jingfang Zhang, Ning Zhu and Chunmin Zhang and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

In The Last Decade

Mei-qing An

13 papers receiving 428 citations

Peers

Mei-qing An
Dongdong Yang China
Changshou Deng China
Bernardo Morales-Castañeda Mexico
Miguel Cienfuegos Germany
Changsheng Wen China
Binping Zhao China
Lingjie Li China
Dongdong Yang China
Mei-qing An
Citations per year, relative to Mei-qing An Mei-qing An (= 1×) peers Dongdong Yang

Countries citing papers authored by Mei-qing An

Since Specialization
Citations

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

Fields of papers citing papers by Mei-qing An

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mei-qing An. 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 Mei-qing An. The network helps show where Mei-qing An may publish in the future.

Co-authorship network of co-authors of Mei-qing An

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

All Works

13 of 13 papers shown
1.
Xiang, Wanli, Yinzhen Li, Ruichun He, & Mei-qing An. (2020). Artificial bee colony algorithm with a pure crossover operation for binary optimization. Computers & Industrial Engineering. 152. 107011–107011. 18 indexed citations
2.
Xiang, Wanli, Yinzhen Li, Ruichun He, Xuelei Meng, & Mei-qing An. (2019). An Improved Artificial Bee Colony Algorithm With Fitness-Based Information. IEEE Access. 7. 41052–41065. 2 indexed citations
3.
Xiang, Wanli, Yinzhen Li, Ruichun He, Xuelei Meng, & Mei-qing An. (2019). A Multistrategy Artificial Bee Colony Algorithm Enlightened by Variable Neighborhood Search. Computational Intelligence and Neuroscience. 2019. 1–19. 5 indexed citations
4.
Xiang, Wanli, Xuelei Meng, Yinzhen Li, Ruichun He, & Mei-qing An. (2017). An improved artificial bee colony algorithm based on the gravity model. Information Sciences. 429. 49–71. 53 indexed citations
5.
Xiang, Wanli, Yinzhen Li, Xuelei Meng, Chunmin Zhang, & Mei-qing An. (2017). A grey artificial bee colony algorithm. Applied Soft Computing. 60. 1–17. 29 indexed citations
6.
Xiang, Wanli, et al.. (2017). A novel artificial bee colony algorithm based on the cosine similarity. Computers & Industrial Engineering. 115. 54–68. 20 indexed citations
7.
Xiang, Wanli, Ning Zhu, Shoufeng Ma, Xuelei Meng, & Mei-qing An. (2015). A dynamic shuffled differential evolution algorithm for data clustering. Neurocomputing. 158. 144–154. 47 indexed citations
8.
Xiang, Wanli, et al.. (2015). An Enhanced Differential Evolution Algorithm Based on Multiple Mutation Strategies. Computational Intelligence and Neuroscience. 2015. 1–15. 24 indexed citations
9.
Xiang, Wanli, Xuelei Meng, & Mei-qing An. (2015). An Alternate Iterative Differential Evolution Algorithm for Parameter Identification of Chaotic Systems. Discrete Dynamics in Nature and Society. 2015. 1–11. 5 indexed citations
10.
Xiang, Wanli, Mei-qing An, Yinzhen Li, Ruichun He, & Jingfang Zhang. (2014). A Novel Discrete Global-Best Harmony Search Algorithm for Solving 0-1 Knapsack Problems. Discrete Dynamics in Nature and Society. 2014. 1–12. 20 indexed citations
11.
Xiang, Wanli, Mei-qing An, Yinzhen Li, Ruichun He, & Jingfang Zhang. (2014). An improved global-best harmony search algorithm for faster optimization. Expert Systems with Applications. 41(13). 5788–5803. 52 indexed citations
12.
Xiang, Wanli, Shoufeng Ma, & Mei-qing An. (2014). hABCDE: A hybrid evolutionary algorithm based on artificial bee colony algorithm and differential evolution. Applied Mathematics and Computation. 238. 370–386. 37 indexed citations
13.
Xiang, Wanli & Mei-qing An. (2012). An efficient and robust artificial bee colony algorithm for numerical optimization. Computers & Operations Research. 40(5). 1256–1265. 130 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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