Peng Wang

4.5k citations
241 papers · 3.5k · 1 hit paper · h-index 32

Impact in

Papers in

Peng Wang

219 papers receiving 3.4k citations

Peng Wang's Hit Papers

A novel hybrid MCDM model combining the SAW, TOPSIS and GRA methods based on experimental design 2016 · 264 citations
2640+3+6Years since publication50100150200250

Peers

Peng Wang
Comparison fields: 5 of 144
  • Ocean Engineering 936
  • Computational Theory and Mathematics 966
  • Management Science and Operations Research 448
  • Statistics, Probability and Uncertainty 232
  • Artificial Intelligence 862
Replace R. Timothy Marler with:
R. Timothy Marler United States
Jean‐Paul Watson United States
N. Srinivas India
Li Li China
Min‐Yuan Cheng Taiwan
Ali Sadollah Iran
Himanshu Jain India
Tapabrata Ray Australia
Singiresu S. Rao United States
Behnam Mohammadi‐Ivatloo Iran
Peng Wang relative to R. Timothy Marler United States R. Timothy Marler's profile →
Citations per field
00.5×3.5×
R. Timothy Marler · 1×
Citations per year

Countries citing papers authored by Peng Wang

Since Specialization
Citations

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

Fields of papers citing papers by Peng Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Peng Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Peng Wang Line = papers co-authored together Peng Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 241 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A novel hybrid MCDM model combining the SAW, TOPSIS and GRA methods based on experimental design
Hit paper breakdown →
2016264
2 2019146
3 2013104
4 201874
5 201573
6 201571
7 201864
8 202064
9 201863
10 201661
11 201859
12 202058
13 201956
14 201752
15 199750
16 202049
17 201847
18 202045
19 202045
20 201942

About Peng Wang

Peng Wang is a scholar working on Ocean Engineering, Computational Theory and Mathematics, Artificial Intelligence, Aerospace Engineering and Computer Vision and Pattern Recognition, having authored 241 papers that have together received 3.5k indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (66 papers), Metaheuristic Optimization Algorithms Research (52 papers), Underwater Vehicles and Communication Systems (38 papers), Robotic Path Planning Algorithms (18 papers), Ship Hydrodynamics and Maneuverability (16 papers), Evolutionary Algorithms and Applications (14 papers), Optimal Experimental Design Methods (14 papers) and Cavitation Phenomena in Pumps (13 papers). The work is most often cited by research in Ocean Engineering (936 citations), Computational Theory and Mathematics (966 citations), Management Science and Operations Research (448 citations), Statistics, Probability and Uncertainty (232 citations) and Artificial Intelligence (862 citations). Peng Wang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Huachao Dong, Baowei Song, Zhouquan Zhu, Xinjing Wang, Yonghu Wang, Zuomin Dong, Jiangtao Shen, Jinglu Li, Shuchao Cao and Peng Meng. Their work appears in journals such as Applied Soft Computing, Ocean Engineering, Structural and Multidisciplinary Optimization, Engineering Optimization and Knowledge-Based Systems.

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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