Weifeng Gao

4.5k total citations · 3 hit papers
107 papers, 3.5k citations indexed

About

Weifeng Gao is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Civil and Structural Engineering. According to data from OpenAlex, Weifeng Gao has authored 107 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Artificial Intelligence, 53 papers in Computational Theory and Mathematics and 10 papers in Civil and Structural Engineering. Recurrent topics in Weifeng Gao's work include Metaheuristic Optimization Algorithms Research (58 papers), Advanced Multi-Objective Optimization Algorithms (48 papers) and Evolutionary Algorithms and Applications (30 papers). Weifeng Gao is often cited by papers focused on Metaheuristic Optimization Algorithms Research (58 papers), Advanced Multi-Objective Optimization Algorithms (48 papers) and Evolutionary Algorithms and Applications (30 papers). Weifeng Gao collaborates with scholars based in China, United States and Hong Kong. Weifeng Gao's co-authors include Sanyang Liu, Lingling Huang, Gary G. Yen, Genghui Li, Maoguo Gong, Qiuzhen Lin, Qingfu Zhang, Cai Dai, Felix T.S. Chan and Hong Li and has published in prestigious journals such as Analytical Biochemistry, International Journal of Molecular Sciences and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Weifeng Gao

96 papers receiving 3.4k citations

Hit Papers

A modified artificial bee colony algorithm 2011 2026 2016 2021 2011 2012 2012 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Weifeng Gao China 26 2.5k 1.5k 446 432 376 107 3.5k
Abdolreza Hatamlou Iran 13 2.6k 1.0× 1.1k 0.8× 514 1.2× 443 1.0× 679 1.8× 25 4.0k
Mohammad H. Nadimi-Shahraki Iran 30 2.2k 0.9× 955 0.7× 475 1.1× 434 1.0× 533 1.4× 77 3.6k
Jagdish Chand Bansal India 28 1.8k 0.7× 683 0.5× 415 0.9× 411 1.0× 577 1.5× 126 3.2k
Sankalap Arora India 19 2.3k 0.9× 976 0.7× 506 1.1× 467 1.1× 719 1.9× 29 3.7k
Qifang Luo China 28 1.7k 0.7× 666 0.5× 427 1.0× 332 0.8× 400 1.1× 127 2.7k
Afshin Faramarzi United States 8 1.9k 0.8× 952 0.7× 440 1.0× 604 1.4× 831 2.2× 9 3.6k
Benyamın Abdollahzadeh Iran 13 1.7k 0.7× 748 0.5× 365 0.8× 492 1.1× 636 1.7× 16 3.1k
Zixing Cai China 25 3.2k 1.3× 2.5k 1.7× 877 2.0× 680 1.6× 439 1.2× 210 5.0k
Rui Mendes Portugal 12 2.6k 1.0× 1.3k 0.9× 220 0.5× 726 1.7× 370 1.0× 24 3.5k
Zhun Fan China 37 2.0k 0.8× 1.7k 1.2× 728 1.6× 684 1.6× 632 1.7× 249 4.6k

Countries citing papers authored by Weifeng Gao

Since Specialization
Citations

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

Fields of papers citing papers by Weifeng Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weifeng Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Weifeng Gao. A scholar is included among the top collaborators of Weifeng Gao 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 Weifeng Gao. Weifeng Gao 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.
Gao, Weifeng, et al.. (2025). Robust decentralized federated learning for heterogeneous and non-ideal networks. Pattern Recognition. 162. 111362–111362.
2.
Li, Hong, et al.. (2025). Neural architecture search with integrated template-modules for efficient defect detection. Expert Systems with Applications. 278. 127211–127211.
3.
Jiang, Siqi, Weifeng Gao, Guozhao Ji, & Aimin Li. (2025). Closed-loop valorization of fly ash: Integrating selective metal extraction and multi-solid-waste geopolymer synthesis for circular economy. Separation and Purification Technology. 374. 133664–133664.
4.
Gao, Weifeng, et al.. (2025). High-order multi-scale neural network method for quasi-static thermo-mechanical problems of composite materials. Applied Mathematical Modelling. 148. 116232–116232. 2 indexed citations
5.
Gao, Weifeng, et al.. (2025). A high-precision method for corn variety identification based on data fusion technology and the PSX-Staking algorithm. Journal of Food Composition and Analysis. 147. 108098–108098.
6.
Gao, Weifeng, et al.. (2024). Higher-order multi-scale physics-informed neural network (HOMS-PINN) method and its convergence analysis for solving elastic problems of authentic composite materials. Journal of Computational and Applied Mathematics. 456. 116223–116223. 11 indexed citations
7.
Gao, Weifeng, et al.. (2024). Effective transferred knowledge identified by bipartite graph for multiobjective multitasking optimization. Knowledge-Based Systems. 290. 111530–111530. 3 indexed citations
8.
Xie, Jin, et al.. (2024). A fully decentralized distributed learning algorithm for latency communication networks. Knowledge-Based Systems. 309. 112829–112829.
9.
Wang, Zhenkun, et al.. (2024). Multiobjective Optimization Problem With Hardly Dominated Boundaries: Benchmark, Analysis, and Indicator-Based Algorithm. IEEE Transactions on Evolutionary Computation. 29(4). 1070–1084. 5 indexed citations
10.
Sun, Yifei, et al.. (2024). Personalized Exercise Group Assembly Using a Two Archive Evolutionary Algorithm. IEEE Transactions on Emerging Topics in Computational Intelligence. 9(3). 2572–2583.
11.
Li, Genghui, Zhenkun Wang, Weifeng Gao, Laizhong Cui, & Qingfu Zhang. (2024). Adaptive Multi/Many-Objective Transformation for Constrained Optimization. IEEE Transactions on Systems Man and Cybernetics Systems. 55(1). 721–734. 4 indexed citations
12.
Zhou, Xinyu, et al.. (2024). Adaptive multi-population artificial bee colony algorithm based on fitness landscape analysis. Applied Soft Computing. 164. 111952–111952. 8 indexed citations
13.
Gao, Weifeng, et al.. (2024). Federated Multidiscriminators Multigenerators for Heterogeneous Industrial IoT. IEEE Transactions on Industrial Informatics. 21(1). 884–893. 1 indexed citations
14.
Gao, Weifeng, et al.. (2023). BiOM: A framework for multimodal multiobjective optimization. Information Sciences. 653. 119750–119750. 7 indexed citations
15.
Gao, Weifeng, et al.. (2023). Evaluation of high oleic sunflower oil oleogels with beeswax, beeswax‐glyceryl monopalmitate, and beeswax‐Span80 in cookie preparation. Journal of the Science of Food and Agriculture. 103(13). 6198–6207. 5 indexed citations
16.
Li, Xuewen, et al.. (2023). A Novel in Duck Myoblasts: The Transcription Factor Retinoid X Receptor Alpha (RXRA) Inhibits Lipid Accumulation by Promoting CD36 Expression. International Journal of Molecular Sciences. 24(2). 1180–1180. 9 indexed citations
17.
Zhang, Lulu, Weifeng Gao, Jin Xie, & Hong Li. (2023). An ordinary differential equation for modeling Halpern fixed-point algorithm. Applied Mathematics Letters. 148. 108889–108889. 3 indexed citations
19.
Gao, Weifeng. (2012). Differential evolution with the search strategy of artificial bee colony algorithm. Kongzhi yu juece. 3 indexed citations
20.
Gao, Weifeng, Sanyang Liu, & Lingling Huang. (2012). A global best artificial bee colony algorithm for global optimization. Journal of Computational and Applied Mathematics. 236(11). 2741–2753. 341 indexed citations breakdown →

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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