Fangjun Kuang

1.4k total citations · 1 hit paper
35 papers, 1.1k citations indexed

About

Fangjun Kuang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Fangjun Kuang has authored 35 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 9 papers in Computer Vision and Pattern Recognition and 6 papers in Control and Systems Engineering. Recurrent topics in Fangjun Kuang's work include Metaheuristic Optimization Algorithms Research (13 papers), Evolutionary Algorithms and Applications (5 papers) and Advanced Multi-Objective Optimization Algorithms (4 papers). Fangjun Kuang is often cited by papers focused on Metaheuristic Optimization Algorithms Research (13 papers), Evolutionary Algorithms and Applications (5 papers) and Advanced Multi-Objective Optimization Algorithms (4 papers). Fangjun Kuang collaborates with scholars based in China, Iran and Vietnam. Fangjun Kuang's co-authors include Siyang Zhang, Weihong Xu, Huiling Chen, Zhong Jin, Ali Asghar Heidari, Zhennao Cai, Caiyang Yu, Chao Ma, Mengxiang Chen and Kai Cheng and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Image Processing and Expert Systems with Applications.

In The Last Decade

Fangjun Kuang

34 papers receiving 1.0k citations

Hit Papers

A novel hybrid KPCA and SVM with GA model for intrusion d... 2014 2026 2018 2022 2014 100 200 300
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.

  1. A novel hybrid KPCA and SVM with GA model for intrusion detection
    2014 332 citations Fangjun Kuang, Weihong Xu et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fangjun Kuang China 17 645 373 231 174 114 35 1.1k
Chuan-Sheng Foo Singapore 17 656 1.0× 224 0.6× 192 0.8× 251 1.4× 54 0.5× 69 1.2k
Amrit Lal Sangal India 15 717 1.1× 564 1.5× 341 1.5× 157 0.9× 243 2.1× 64 1.6k
Aijia Ouyang China 19 424 0.7× 242 0.6× 48 0.2× 250 1.4× 130 1.1× 62 1.1k
Yan Xiong China 19 329 0.5× 330 0.9× 156 0.7× 159 0.9× 40 0.4× 157 1.2k
Juan Zhao China 19 636 1.0× 168 0.5× 81 0.4× 206 1.2× 221 1.9× 106 1.1k
Xiao Chen China 20 443 0.7× 485 1.3× 206 0.9× 458 2.6× 184 1.6× 130 2.1k
M. Markou United Kingdom 9 1.2k 1.8× 365 1.0× 301 1.3× 259 1.5× 41 0.4× 16 1.7k
Zaer S. Abo‐Hammour Jordan 16 414 0.6× 136 0.4× 74 0.3× 173 1.0× 139 1.2× 35 1.5k

Countries citing papers authored by Fangjun Kuang

Since Specialization
Citations

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

Fields of papers citing papers by Fangjun Kuang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fangjun Kuang

This figure shows the co-authorship network connecting the top 25 collaborators of Fangjun Kuang. A scholar is included among the top collaborators of Fangjun Kuang 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 Fangjun Kuang. Fangjun Kuang 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.
Zheng, Yashuang, et al.. (2025). RIME optimization with dynamic multi-dimensional random mechanism and Nelder–Mead simplex for photovoltaic parameter estimation. Scientific Reports. 15(1). 20951–20951. 1 indexed citations
2.
3.
Kuang, Fangjun, et al.. (2023). Static photovoltaic models’ parameter extraction using reinforcement learning strategy adapted local gradient Nelder-Mead Runge Kutta method. Applied Intelligence. 53(20). 24106–24141. 9 indexed citations
4.
Chen, Chi, et al.. (2023). A grade-based search adaptive random slime mould optimizer for lupus nephritis image segmentation. Computers in Biology and Medicine. 160. 106950–106950. 25 indexed citations
5.
Heidari, Ali Asghar, et al.. (2023). Gaussian bare-bone slime mould algorithm: performance optimization and case studies on truss structures. Artificial Intelligence Review. 56(9). 9051–9087. 20 indexed citations
6.
Li, Jie, Jin Xiao, Shijia Wang, et al.. (2023). Pneumothorax prediction using a foraging and hunting based ant colony optimizer assisted support vector machine. Computers in Biology and Medicine. 161. 106948–106948. 2 indexed citations
7.
Liu, Jia-Cong, Jiahui Wei, Ali Asghar Heidari, et al.. (2022). Chaotic simulated annealing multi-verse optimization enhanced kernel extreme learning machine for medical diagnosis. Computers in Biology and Medicine. 144. 105356–105356. 38 indexed citations
8.
Heidari, Ali Asghar, Fangjun Kuang, Ashraf Khalil, et al.. (2022). Enhanced Gaussian bare-bones grasshopper optimization: Mitigating the performance concerns for feature selection. Expert Systems with Applications. 212. 118642–118642. 36 indexed citations
9.
Li, Yuan, Fangjun Kuang, Siyang Zhang, & Huiling Chen. (2022). The Gaussian Mutational Barebone Dragonfly Algorithm: From Design to Analysis. Symmetry. 14(2). 331–331. 4 indexed citations
10.
Zhu, Wei, et al.. (2022). An efficient multi-threshold image segmentation for skin cancer using boosting whale optimizer. Computers in Biology and Medicine. 151(Pt A). 106227–106227. 33 indexed citations
11.
Kuang, Fangjun, et al.. (2022). Pruned RNN-T for fast, memory-efficient ASR training. Interspeech 2022. 2068–2072. 22 indexed citations
12.
Yu, Caiyang, Mengxiang Chen, Kai Cheng, et al.. (2021). SGOA: annealing-behaved grasshopper optimizer for global tasks. Engineering With Computers. 38(S5). 3761–3788. 126 indexed citations
13.
Kuang, Fangjun & Siyang Zhang. (2017). A Novel Network Intrusion Detection Based on Support Vector Machine and Tent Chaos Artificial Bee Colony Algorithm.. 2. 195–204. 6 indexed citations
14.
15.
Kuang, Fangjun, Zhong Jin, Weihong Xu, & Siyang Zhang. (2014). A novel chaotic artificial bee colony algorithm based on Tent map. 235–241. 30 indexed citations
16.
Chen, Yuantao, Weihong Xu, Fangjun Kuang, & Shangbing Gao. (2013). The Research and Application of Visual Saliency and Adaptive Support Vector Machine in Target Tracking Field. Computational and Mathematical Methods in Medicine. 2013. 1–8. 5 indexed citations
17.
Hu, Rong, et al.. (2012). An Improved Incremental Singular Value Decomposition. International Journal of Advancements in Computing Technology. 4(2). 95–102. 2 indexed citations
18.
Chen, Yuantao, et al.. (2012). Complete Fuzzy LDA Algorithm in Image Segmentation. INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences. 4(5). 53–60. 2 indexed citations
19.
Chen, Yuantao, et al.. (2012). A Novel Image Segmentation Algorithm Based on Visual Saliency. International Journal of Digital Content Technology and its Applications. 6(4). 133–140. 2 indexed citations
20.
Wang, Yan, et al.. (2012). Information-centric industrial Internet of Things: Service model. 99. 1123–1128. 5 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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