Rong‐Long Wang

748 total citations
73 papers, 491 citations indexed

About

Rong‐Long Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Rong‐Long Wang has authored 73 papers receiving a total of 491 indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Artificial Intelligence, 17 papers in Computer Vision and Pattern Recognition and 16 papers in Computational Theory and Mathematics. Recurrent topics in Rong‐Long Wang's work include Metaheuristic Optimization Algorithms Research (31 papers), Neural Networks and Applications (23 papers) and Advanced Multi-Objective Optimization Algorithms (12 papers). Rong‐Long Wang is often cited by papers focused on Metaheuristic Optimization Algorithms Research (31 papers), Neural Networks and Applications (23 papers) and Advanced Multi-Objective Optimization Algorithms (12 papers). Rong‐Long Wang collaborates with scholars based in Japan, China and Hong Kong. Rong‐Long Wang's co-authors include Shangce Gao, Zheng Tang, Kozo Okazaki, Jin‐Siang Shaw, Pei‐Hao Chen, Qi Cao, Zhenyu Lei, Zhiqiang Chen, Zhiming Zhang and Yuki Todo and has published in prestigious journals such as Expert Systems with Applications, Neural Computation and Neurocomputing.

In The Last Decade

Rong‐Long Wang

63 papers receiving 462 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rong‐Long Wang Japan 12 225 92 62 56 56 73 491
Giorgio Roffo Italy 10 224 1.0× 39 0.4× 162 2.6× 19 0.3× 19 0.3× 17 494
Simone Melzi Italy 14 209 0.9× 51 0.6× 449 7.2× 18 0.3× 16 0.3× 37 874
Habib Dhahri Saudi Arabia 17 383 1.7× 40 0.4× 97 1.6× 94 1.7× 77 1.4× 46 675
Arif Gülten Türkiye 12 207 0.9× 53 0.6× 195 3.1× 57 1.0× 83 1.5× 36 606
Tobias Glasmachers Germany 16 406 1.8× 112 1.2× 133 2.1× 30 0.5× 49 0.9× 43 741
Xuan He China 12 134 0.6× 76 0.8× 23 0.4× 209 3.7× 155 2.8× 55 673
Hamid Reza Hassanzadeh United States 6 256 1.1× 50 0.5× 57 0.9× 18 0.3× 28 0.5× 9 657

Countries citing papers authored by Rong‐Long Wang

Since Specialization
Citations

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

Fields of papers citing papers by Rong‐Long Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rong‐Long Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Rong‐Long Wang. A scholar is included among the top collaborators of Rong‐Long 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 Rong‐Long Wang. Rong‐Long Wang 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.
Zhang, Zhiming, et al.. (2024). Dendritic Deep Learning for Medical Segmentation. IEEE/CAA Journal of Automatica Sinica. 11(3). 803–805. 25 indexed citations
2.
Fan, Xiao‐Wei, et al.. (2024). Transformer–BiLSTM Fusion Neural Network for Short-Term PV Output Prediction Based on NRBO Algorithm and VMD. Applied Sciences. 14(24). 11991–11991. 5 indexed citations
3.
Wang, Ziqian, et al.. (2024). Feature selection with clustering probabilistic particle swarm optimization. International Journal of Machine Learning and Cybernetics. 15(9). 3599–3617. 6 indexed citations
4.
Wang, Rong‐Long, et al.. (2023). Elite‐of‐the‐Elites Driven Five‐Layered Gravitational Search Algorithm for Optimization. IEEJ Transactions on Electrical and Electronic Engineering. 18(12). 1958–1960. 3 indexed citations
5.
Yang, Haichuan, et al.. (2023). A Non-Revisiting Equilibrium Optimizer Algorithm. IEICE Transactions on Information and Systems. E106.D(3). 365–373. 2 indexed citations
6.
Wang, Kaiyu, et al.. (2023). Hierarchical Manta Ray Foraging Optimization with Weighted Fitness-Distance Balance Selection. International Journal of Computational Intelligence Systems. 16(1). 10 indexed citations
7.
Liu, Zhipeng, et al.. (2023). Dendritic Learning-Based DenseNet for Classification. 112–115. 2 indexed citations
8.
Li, Jing, et al.. (2021). CircZKSCAN1 Suppresses Hepatocellular Carcinoma Tumorigenesis by Regulating miR-873-5p/Downregulation of Deleted in Liver Cancer 1. Digestive Diseases and Sciences. 66(12). 4374–4383. 17 indexed citations
9.
Chen, Pei‐Hao, et al.. (2013). Gait Disorders in Parkinson's Disease: Assessment and Management. International journal of gerontology. 7(4). 189–193. 81 indexed citations
10.
Wang, Rong‐Long, et al.. (2012). SELF-EVOLVING ANT COLONY OPTIMIZATION AND ITS APPLICATION TO TRAVELING SALESMAN PROBLEM. International journal of innovative computing, information & control. 8. 8311–8321. 4 indexed citations
11.
Zhang, Pei, et al.. (2006). An Effective Algorithm for the Minimum Set Cover Problem. 52. 3032–3035. 1 indexed citations
12.
Wang, Jiahai, Zheng Tang, & Rong‐Long Wang. (2004). A Chaotic Maximum Neural Network for Maximum Clique Problem. IEICE Transactions on Information and Systems. 87(7). 1953–1961. 2 indexed citations
13.
Tang, Zheng, et al.. (2004). A fast and reliable approach to TSP using positively self-feedbacked Hopfield networks. Society of Instrument and Control Engineers of Japan. 2. 999–1004. 1 indexed citations
14.
Wang, Rong‐Long, Zhimin Tang, & Qi Cao. (2004). A Hopfield Network Learning Method for Bipartite Subgraph Problem. IEEE Transactions on Neural Networks. 15(6). 1458–1465. 4 indexed citations
15.
Wang, Jiahai, et al.. (2004). OPTIMAL COMPETITIVE HOPFIELD NETWORK WITH STOCHASTIC DYNAMICS FOR MAXIMUM CUT PROBLEM. International Journal of Neural Systems. 14(4). 257–265.
16.
Tang, Zheng, et al.. (2004). A Fast and Reliable Approach to TSP using Positively Self-feedbacked Hopfield Networks. IEEJ Transactions on Electronics Information and Systems. 124(11). 2353–2358. 1 indexed citations
17.
Wang, Rong‐Long, et al.. (2003). Solving Maximum Cut Problem Using Improved Hop field Neural Network. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 86(3). 722–729. 1 indexed citations
18.
Cao, Qi, et al.. (2003). A Local search based learning method for multiple-valued logic networks. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 86(7). 1876–1884. 6 indexed citations
19.
Wang, Rong‐Long, Zheng Tang, & Qi Cao. (2002). A Near-Optimum Parallel Algorithm for Bipartite Subgraph Problem Using the Hopfield Neural Network Learning. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 85(2). 497–504. 3 indexed citations
20.
Wang, Rong‐Long, Zheng Tang, & Qi Cao. (2002). A New Updating Procedure in the Hopfield-Type Network and Its Application to N-Queens Problem. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 85(10). 2368–2372. 1 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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