Gai‐Ge Wang

16.1k total citations · 9 hit papers
189 papers, 12.9k citations indexed

About

Gai‐Ge Wang is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Gai‐Ge Wang has authored 189 papers receiving a total of 12.9k indexed citations (citations by other indexed papers that have themselves been cited), including 125 papers in Artificial Intelligence, 72 papers in Computational Theory and Mathematics and 27 papers in Computer Vision and Pattern Recognition. Recurrent topics in Gai‐Ge Wang's work include Metaheuristic Optimization Algorithms Research (114 papers), Advanced Multi-Objective Optimization Algorithms (72 papers) and Evolutionary Algorithms and Applications (55 papers). Gai‐Ge Wang is often cited by papers focused on Metaheuristic Optimization Algorithms Research (114 papers), Advanced Multi-Objective Optimization Algorithms (72 papers) and Evolutionary Algorithms and Applications (55 papers). Gai‐Ge Wang collaborates with scholars based in China, United States and Canada. Gai‐Ge Wang's co-authors include Suash Deb, Amir H. Gandomi, Amir H. Alavi, Leandro dos Santos Coelho, Zhihua Cui, Lihong Guo, Heqi Wang, Hong Duan, Yanhong Feng and Witold Pedrycz and has published in prestigious journals such as SHILAP Revista de lepidopterología, Chemical Engineering Journal and Applied Energy.

In The Last Decade

Gai‐Ge Wang

183 papers receiving 12.5k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Monarch butterfly optimization

2015 814 citations Gai‐Ge Wang et al. profile →
Moth search algorithm: a bio-inspired metaheuristic algorithm for global optimization problems

2016 663 citations Gai‐Ge Wang profile →
Elephant Herding Optimization

2015 506 citations Gai‐Ge Wang et al. profile →
Chaotic Krill Herd algorithm

2014 481 citations Gai‐Ge Wang et al. Information Sciences profile →
Detection of Malicious Code Variants Based on Deep Learning

2018 459 citations Gai‐Ge Wang et al. profile →
Earthworm optimisation algorithm: a bio-inspired metaheuristic algorithm for global optimisation problems

2018 312 citations Gai‐Ge Wang et al. profile →
Solving Fuzzy Job-Shop Scheduling Problem Using DE Algorithm Improved by a Selection Mechanism

2020 237 citations Gai‐Ge Wang et al. profile →
Solving Multiobjective Fuzzy Job-Shop Scheduling Problem by a Hybrid Adaptive Differential Evolution Algorithm

2022 207 citations Gai‐Ge Wang et al. profile →
ConvUNeXt: An efficient convolution neural network for medical image segmentation

2022 187 citations Muwei Jian, Gai‐Ge Wang et al. profile →

Author Peers

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

Author						Papers	Cites
Gai‐Ge Wang	7.3k	3.4k	1.9k	1.7k	1.6k	189	12.9k
Bahriye Akay	7.2k 1.0×	3.1k 0.9×	2.0k 1.0×	2.0k 1.2×	1.4k 0.9×	56	13.5k
Suash Deb	6.5k 0.9×	2.8k 0.8×	2.5k 1.3×	1.5k 0.9×	1.0k 0.6×	93	12.3k
Yuhui Shi	7.9k 1.1×	3.6k 1.1×	2.6k 1.3×	1.7k 1.0×	1.2k 0.8×	240	14.7k
Andries P. Engelbrecht	9.0k 1.2×	4.5k 1.3×	1.3k 0.7×	1.4k 0.8×	891 0.6×	366	13.5k
Zhi‐Hui Zhan	8.2k 1.1×	5.0k 1.5×	1.4k 0.7×	1.2k 0.7×	1.2k 0.8×	260	13.1k
Majdi Mafarja	7.9k 1.1×	2.7k 0.8×	1.7k 0.9×	2.1k 1.2×	631 0.4×	87	12.6k
Ibrahim Aljarah	8.0k 1.1×	2.4k 0.7×	2.0k 1.0×	1.7k 1.0×	633 0.4×	117	13.3k
Yew-Soon Ong	10.7k 1.5×	7.3k 2.2×	1.2k 0.6×	1.7k 1.0×	1.6k 1.0×	448	17.4k
Mauro Birattari	5.0k 0.7×	2.1k 0.6×	1.2k 0.6×	1.5k 0.9×	1.9k 1.2×	178	11.3k
Essam H. Houssein	6.3k 0.9×	2.2k 0.6×	2.4k 1.3×	1.7k 1.0×	586 0.4×	259	11.9k

Countries citing papers authored by Gai‐Ge Wang

Since Specialization

Citations

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

Fields of papers citing papers by Gai‐Ge Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gai‐Ge Wang. 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 Gai‐Ge Wang. The network helps show where Gai‐Ge Wang may publish in the future.

Co-authorship network of co-authors of Gai‐Ge Wang

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wang, Yong, et al.. (2025). A dynamic multi-objective optimization based on knowledge prediction and density clustering strategy. Applied Soft Computing. 175. 113099–113099.

Lu, Bibo, et al.. (2025). NGSTGAN: N-Gram Swin Transformer and Multi-Attention U-Net Discriminator for Efficient Multi-Spectral Remote Sensing Image Super-Resolution. Remote Sensing. 17(12). 2079–2079. 3 indexed citations

Wang, Jian, Gai‐Ge Wang, Yong Zhang, et al.. (2025). A two-mode offspring generation selection mechanism with co-evolution for sparse large-scale multiobjective optimization. Information Sciences. 718. 122337–122337. 1 indexed citations

Wang, Gai‐Ge, et al.. (2024). A Tree-Based Multiobjective Evolutionary Algorithm for Energy-Efficient Hybrid Flow-Shop Scheduling. IEEE Transactions on Evolutionary Computation. 29(6). 2313–2327. 5 indexed citations

Wang, Yong, et al.. (2024). An Adaptive Multistrategy Algorithm Based on Extent of Environmental Change for Dynamic Multiobjective Optimization. IEEE Transactions on Evolutionary Computation. 29(5). 1937–1951. 4 indexed citations

Wang, Yong, et al.. (2024). Impact of physical and attention mechanisms on U-Net for SST forecasting. 2(1). 3 indexed citations

Wang, Yong, et al.. (2024). Improving Test Data Generation for MPI Program Path Coverage With FERPSO-IMPR and Surrogate-Assisted Models. IEEE Transactions on Software Engineering. 50(3). 495–511. 1 indexed citations

Lu, Bibo, et al.. (2024). SSFAN: A Compact and Efficient Spectral-Spatial Feature Extraction and Attention-Based Neural Network for Hyperspectral Image Classification. Remote Sensing. 16(22). 4202–4202. 1 indexed citations

Jian, Muwei, et al.. (2023). YOLO-AA: an efficient object detection model via strengthening fusion context information. Multimedia Tools and Applications. 83(4). 10661–10676. 3 indexed citations

10.

Qu, Haipeng, et al.. (2023). A systematic review of fuzzing. Soft Computing. 28(6). 5493–5522. 11 indexed citations

11.

Wang, Yong, et al.. (2023). Hierarchical learning particle swarm optimization using fuzzy logic. Expert Systems with Applications. 232. 120759–120759. 29 indexed citations

12.

Jian, Muwei, Hongyu Chen, Tao Chen, Xiaoguang Li, & Gai‐Ge Wang. (2023). Triple-DRNet: A triple-cascade convolution neural network for diabetic retinopathy grading using fundus images. Computers in Biology and Medicine. 155. 106631–106631. 42 indexed citations

13.

Wang, Gai‐Ge, et al.. (2023). A dual-population multi-objective evolutionary algorithm driven by generative adversarial networks for benchmarking and protein-peptide docking. Computers in Biology and Medicine. 168. 107727–107727. 4 indexed citations

14.

Yang, Wei, et al.. (2023). Landsat-8 to Sentinel-2 Satellite Imagery Super-Resolution-Based Multiscale Dilated Transformer Generative Adversarial Networks. Remote Sensing. 15(22). 5272–5272. 6 indexed citations

15.

Ma, Lianbo, Yang Liu, Guo Yu, et al.. (2023). Decomposition-Based Multiobjective Optimization for Variable-Length Mixed-Variable Pareto Optimization and Its Application in Cloud Service Allocation. IEEE Transactions on Systems Man and Cybernetics Systems. 53(11). 7138–7151. 10 indexed citations

16.

Jian, Muwei, et al.. (2023). AMSUnet: A neural network using atrous multi-scale convolution for medical image segmentation. Computers in Biology and Medicine. 162. 107120–107120. 44 indexed citations

17.

Gao, Jiechao, et al.. (2022). Redemptive Resource Sharing and Allocation Scheme for Internet of Things-Assisted Smart Healthcare Systems. IEEE Journal of Biomedical and Health Informatics. 26(8). 4238–4247. 6 indexed citations

18.

Feng, Yanhong, Xu Yu, & Gai‐Ge Wang. (2019). A Novel Monarch Butterfly Optimization with Global Position Updating Operator for Large-Scale 0-1 Knapsack Problems. Mathematics. 7(11). 1056–1056. 23 indexed citations

19.

El‐Sehiemy, Ragab A., et al.. (2017). Elephant Herding Optimization for Solving Non-convex Optimal Power Flow Problem. SHILAP Revista de lepidopterología. 14 indexed citations

20.

Feng, Yanhong, et al.. (2014). An Effective Hybrid Cuckoo Search Algorithm with Improved Shuffled Frog Leaping Algorithm for 0-1 Knapsack Problems. Computational Intelligence and Neuroscience. 2014. 1–17. 23 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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