Chuan-Kang Ting

1.8k total citations
75 papers, 1.1k citations indexed

About

Chuan-Kang Ting is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Chuan-Kang Ting has authored 75 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Artificial Intelligence, 22 papers in Computational Theory and Mathematics and 18 papers in Computer Vision and Pattern Recognition. Recurrent topics in Chuan-Kang Ting's work include Metaheuristic Optimization Algorithms Research (29 papers), Evolutionary Algorithms and Applications (26 papers) and Advanced Multi-Objective Optimization Algorithms (21 papers). Chuan-Kang Ting is often cited by papers focused on Metaheuristic Optimization Algorithms Research (29 papers), Evolutionary Algorithms and Applications (26 papers) and Advanced Multi-Objective Optimization Algorithms (21 papers). Chuan-Kang Ting collaborates with scholars based in Taiwan, Germany and United States. Chuan-Kang Ting's co-authors include Chien‐Hung Liu, Chung‐Nan Lee, Xin-Lan Liao, Chih‐Chung Lai, Jain-Shing Wu, Sheng-Tun Li, Tzung‐Pei Hong, Yu‐Hsuan Huang, Cheng‐Jian Lin and Shih-Chieh Su and has published in prestigious journals such as Bioinformatics, PLoS ONE and Expert Systems with Applications.

In The Last Decade

Chuan-Kang Ting

71 papers receiving 1.1k citations

Peers

Chuan-Kang Ting
Chuan-Kang Ting
Citations per year, relative to Chuan-Kang Ting Chuan-Kang Ting (= 1×) peers Hamed Shah‐Hosseini

Countries citing papers authored by Chuan-Kang Ting

Since Specialization
Citations

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

Fields of papers citing papers by Chuan-Kang Ting

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chuan-Kang Ting. 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 Chuan-Kang Ting. The network helps show where Chuan-Kang Ting may publish in the future.

Co-authorship network of co-authors of Chuan-Kang Ting

This figure shows the co-authorship network connecting the top 25 collaborators of Chuan-Kang Ting. A scholar is included among the top collaborators of Chuan-Kang Ting 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 Chuan-Kang Ting. Chuan-Kang Ting 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
2.
Ting, Chuan-Kang, et al.. (2023). Adjusting Infeasible Regions in the Constrained Multiobjective Optimization Problem. 1 indexed citations
3.
Ting, Chuan-Kang, et al.. (2022). Searching Crease Patterns by Genetic Algorithm for Origami Design. 77. 1–8. 1 indexed citations
4.
Ting, Chuan-Kang. (2020). Surfing the Waves of Computational Intelligence [Editor's Remarks]. IEEE Computational Intelligence Magazine. 15(1). 2–2. 1 indexed citations
5.
6.
Ting, Chuan-Kang, et al.. (2018). Fitness Inheritance Assisted MOEA/D-CMAES for Complex Multi-Objective Optimization Problems. 1–8. 4 indexed citations
7.
8.
Ting, Chuan-Kang, et al.. (2017). Evolutionary many-tasking based on biocoenosis through symbiosis: A framework and benchmark problems. 2266–2273. 78 indexed citations
9.
Ting, Chuan-Kang, et al.. (2017). Parting ways and reallocating resources in evolutionary multitasking. 2404–2411. 82 indexed citations
11.
Liu, Chien‐Hung & Chuan-Kang Ting. (2016). Computational Intelligence in Music Composition: A Survey. IEEE Transactions on Emerging Topics in Computational Intelligence. 1(1). 2–15. 45 indexed citations
12.
Ting, Chuan-Kang, et al.. (2012). Extending the lifetime of dynamic wireless sensor networks by genetic algorithm. Zenodo (CERN European Organization for Nuclear Research). 19. 1–8. 9 indexed citations
13.
Su, Shih-Chieh, Cheng‐Jian Lin, & Chuan-Kang Ting. (2011). An effective hybrid of hill climbing and genetic algorithm for 2D triangular protein structure prediction. Proteome Science. 9(S1). S19–S19. 25 indexed citations
14.
Hong, Tzung‐Pei, Chuan-Kang Ting, & Oliver Krämer. (2010). Theory and Applications of Evolutionary Computation. Applied Computational Intelligence and Soft Computing. 2010. 1–2. 2 indexed citations
15.
Su, Shih-Chieh, Cheng‐Jian Lin, & Chuan-Kang Ting. (2010). An efficient hybrid of hill-climbing and genetic algorithm for 2D triangular protein structure prediction. 51–56. 2 indexed citations
16.
Liao, Xin-Lan & Chuan-Kang Ting. (2010). An evolutionary approach for the selective pickup and delivery problem. 1–8. 11 indexed citations
17.
Ting, Chuan-Kang, et al.. (2009). Wireless Heterogeneous Transmitter Placement Using Multiobjective Variable-Length Genetic Algorithm. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 39(4). 945–958. 70 indexed citations
18.
Ting, Chuan-Kang, et al.. (2008). Extending wireless sensor network lifetime through order-based genetic algorithm. Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics. 1434–1439. 5 indexed citations
19.
Ting, Chuan-Kang. (2005). On the Convergence of Multi-Parent Genetic Algorithms. 1. 396–403. 3 indexed citations
20.
Krämer, Oliver, Chuan-Kang Ting, & Hans Kleine Büning. (2005). A mutation operator for evolution strategies to handle constrained problems. 917–918. 3 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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