Changting Zhong

1.5k total citations · 3 hit papers
18 papers, 971 citations indexed

About

Changting Zhong is a scholar working on Computational Theory and Mathematics, Statistics, Probability and Uncertainty and Artificial Intelligence. According to data from OpenAlex, Changting Zhong has authored 18 papers receiving a total of 971 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computational Theory and Mathematics, 9 papers in Statistics, Probability and Uncertainty and 8 papers in Artificial Intelligence. Recurrent topics in Changting Zhong's work include Advanced Multi-Objective Optimization Algorithms (11 papers), Probabilistic and Robust Engineering Design (9 papers) and Metaheuristic Optimization Algorithms Research (7 papers). Changting Zhong is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (11 papers), Probabilistic and Robust Engineering Design (9 papers) and Metaheuristic Optimization Algorithms Research (7 papers). Changting Zhong collaborates with scholars based in China, United Kingdom and Australia. Changting Zhong's co-authors include Zeng Meng, Gang Li, Gang Li, Wanxin He, Ali Rıza Yıldız, Seyedali Mirjalili, Haijiang Li, Betül Sultan Yıldız, Chao Dang and Gang Zhao and has published in prestigious journals such as Expert Systems with Applications, Computer Methods in Applied Mechanics and Engineering and Applied Soft Computing.

In The Last Decade

Changting Zhong

16 papers receiving 934 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.

Beluga whale optimization: A novel nature-inspired metaheuristic algorithm

2022 547 citations Changting Zhong, Gang Li et al. Knowledge-Based Systems profile →
Application of state-of-the-art multiobjective metaheuristic algorithms in reliability-based design optimization: a comparative study

2023 93 citations Zeng Meng, Betül Sultan Yıldız et al. Structural and Multidisciplinary Optimization profile →
Starfish optimization algorithm (SFOA): a bio-inspired metaheuristic algorithm for global optimization compared with 100 optimizers

2024 73 citations Changting Zhong, Zeng Meng et al. Neural Computing and Applications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Changting Zhong China	10	411	265	184	135	108	18	971
Dawei Zhan China	11	304 0.7×	371 1.4×	95 0.5×	81 0.6×	65 0.6×	21	854
Rituparna Datta India	14	328 0.8×	352 1.3×	85 0.5×	114 0.8×	73 0.7×	48	710
Osman Kaan Erol Türkiye	7	768 1.9×	493 1.9×	209 1.1×	232 1.7×	297 2.8×	13	1.4k
Qinghua Gu China	18	314 0.8×	263 1.0×	97 0.5×	130 1.0×	66 0.6×	63	861
Hammoudi Abderazek Algeria	14	471 1.1×	396 1.5×	143 0.8×	144 1.1×	195 1.8×	32	1.0k
Mohammed Jameel Yemen	9	714 1.7×	351 1.3×	227 1.2×	201 1.5×	52 0.5×	19	1.3k
Yiying Zhang China	16	686 1.7×	263 1.0×	228 1.2×	158 1.2×	49 0.5×	23	1.1k
Huachao Dong China	19	493 1.2×	644 2.4×	49 0.3×	65 0.5×	91 0.8×	81	1.1k
Itziar Landa-Torres Spain	14	323 0.8×	136 0.5×	162 0.9×	127 0.9×	45 0.4×	28	829

Countries citing papers authored by Changting Zhong

Since Specialization

Citations

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

Fields of papers citing papers by Changting Zhong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Changting Zhong

This figure shows the co-authorship network connecting the top 25 collaborators of Changting Zhong. A scholar is included among the top collaborators of Changting Zhong 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 Changting Zhong. Changting Zhong 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:

18 of 18 papers shown

Zhong, Changting, et al.. (2026). Opposition and reinforcement learning growth-starfish optimization algorithm for engineering design and feature selection. Knowledge-Based Systems. 338. 115522–115522.

Meng, Zeng, et al.. (2025). Data-driven reliability-based topology optimization by using the extended multi scale finite element method and neural network approach. Computer Methods in Applied Mechanics and Engineering. 438. 117837–117837. 8 indexed citations

Meng, Zeng, et al.. (2025). Non-iterative method for reliability-based topology optimization of static and dynamic problems with uncertain-but-bounded parameters. Computer Methods in Applied Mechanics and Engineering. 448. 118456–118456.

Li, Gang, et al.. (2024). A data-driven maximum entropy method for probability uncertainty analysis based on the B-spline theory. Probabilistic Engineering Mechanics. 78. 103688–103688. 1 indexed citations

He, Wanxin, et al.. (2024). An adaptive data-driven subspace polynomial dimensional decomposition for high-dimensional uncertainty quantification based on maximum entropy method and sparse Bayesian learning. Structural Safety. 108. 102450–102450. 5 indexed citations

Zhong, Changting, et al.. (2024). Starfish optimization algorithm (SFOA): a bio-inspired metaheuristic algorithm for global optimization compared with 100 optimizers. Neural Computing and Applications. 37(5). 3641–3683. 73 indexed citations breakdown →

Zhong, Changting, Gang Li, Zeng Meng, Haijiang Li, & Wanxin He. (2023). A self-adaptive quantum equilibrium optimizer with artificial bee colony for feature selection. Computers in Biology and Medicine. 153. 106520–106520. 39 indexed citations

He, Wanxin, Gang Li, Changting Zhong, & Yixuan Wang. (2023). A novel data-driven sparse polynomial chaos expansion for high-dimensional problems based on active subspace and sparse Bayesian learning. Structural and Multidisciplinary Optimization. 66(1). 6 indexed citations

Meng, Zeng, Betül Sultan Yıldız, Gang Li, et al.. (2023). Application of state-of-the-art multiobjective metaheuristic algorithms in reliability-based design optimization: a comparative study. Structural and Multidisciplinary Optimization. 66(8). 93 indexed citations breakdown →

10.

Zhong, Changting, et al.. (2023). Multi-objective SHADE with manta ray foraging optimizer for structural design problems. Applied Soft Computing. 134. 110016–110016. 21 indexed citations

11.

Zhong, Changting, Gang Li, & Zeng Meng. (2022). Beluga whale optimization: A novel nature-inspired metaheuristic algorithm. Knowledge-Based Systems. 251. 109215–109215. 547 indexed citations breakdown →

12.

Liu, Ye, Gang Zhao, Gang Li, Wanxin He, & Changting Zhong. (2022). Analytical robust design optimization based on a hybrid surrogate model by combining polynomial chaos expansion and Gaussian kernel. Structural and Multidisciplinary Optimization. 65(11). 9 indexed citations

13.

Zhong, Changting, et al.. (2022). Correction to: A hybrid teaching–learning slime mould algorithm for global optimization and reliability-based design optimization problems. Neural Computing and Applications. 34(23). 21417–21418. 1 indexed citations

14.

Zhong, Changting, Gang Li, Zeng Meng, & Wanxin He. (2022). Opposition-based learning equilibrium optimizer with Levy flight and evolutionary population dynamics for high-dimensional global optimization problems. Expert Systems with Applications. 215. 119303–119303. 47 indexed citations

15.

Zhong, Changting, et al.. (2022). A hybrid teaching–learning slime mould algorithm for global optimization and reliability-based design optimization problems. Neural Computing and Applications. 34(19). 16617–16642. 23 indexed citations

16.

Zhong, Changting & Gang Li. (2021). Comprehensive learning Harris hawks-equilibrium optimization with terminal replacement mechanism for constrained optimization problems. Expert Systems with Applications. 192. 116432–116432. 33 indexed citations

17.

Zhong, Changting, et al.. (2020). Structural reliability assessment by salp swarm algorithm–based FORM. Quality and Reliability Engineering International. 36(4). 1224–1244. 22 indexed citations

18.

Zhong, Changting, et al.. (2020). First-order reliability method based on Harris Hawks Optimization for high-dimensional reliability analysis. Structural and Multidisciplinary Optimization. 62(4). 1951–1968. 43 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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