Ya-Hui Jia

1.0k citations
35 papers · 760 · h-index 13

Impact in

Papers in

Ya-Hui Jia

30 papers receiving 749 citations

Peers

Ya-Hui Jia
Comparison fields: 5 of 69
  • Industrial and Manufacturing Engineering 262
  • Computational Theory and Mathematics 180
  • Artificial Intelligence 326
  • Automotive Engineering 109
  • Building and Construction 70
Replace Ayad Turky with:
Ayad Turky Australia
Roberto Carballedo Spain
Zakir Hussain Ahmed Saudi Arabia
Li‐Pei Wong Malaysia
Belaïd Ahiod Morocco
Surafel Luleseged Tilahun Ethiopia
Max Manfrin Belgium
Mostafa Mahi Iran
L. M. Gambardella Switzerland
Junqi Zhang China
Ya-Hui Jia relative to Ayad Turky Australia Ayad Turky's profile →
Citations per field
00.5×3.9×
Ayad Turky · 1×
Citations per year

Countries citing papers authored by Ya-Hui Jia

Since Specialization
Citations

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

Fields of papers citing papers by Ya-Hui Jia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ya-Hui Jia. 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 Ya-Hui Jia. The network helps show where Ya-Hui Jia may publish in the future.

Co-authors

The 25 scholars most cited alongside Ya-Hui Jia, 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 Ya-Hui Jia Line = papers co-authored together Ya-Hui Jia links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021151
2 201883
3 201778
4 201971
5 201862
6 202255
7 202346
8 202139
9 202038
10 202123
11 202117
12 201917
13 202213
14 202310
15 20209
16 20209
17 20238
18 20147
19 20245
20 20144

About Ya-Hui Jia

Ya-Hui Jia is a scholar working on Artificial Intelligence, Industrial and Manufacturing Engineering, Computer Vision and Pattern Recognition, Computer Networks and Communications and Automotive Engineering, having authored 35 papers that have together received 760 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (14 papers), Vehicle Routing Optimization Methods (11 papers), Robotic Path Planning Algorithms (7 papers), Advanced Multi-Objective Optimization Algorithms (5 papers), Transportation and Mobility Innovations (4 papers), Evolutionary Algorithms and Applications (4 papers), Distributed Control Multi-Agent Systems (4 papers) and Smart Parking Systems Research (3 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (262 citations), Computational Theory and Mathematics (180 citations), Artificial Intelligence (326 citations), Automotive Engineering (109 citations) and Building and Construction (70 citations). Ya-Hui Jia has collaborated with scholars based in China, New Zealand and South Korea. Frequent co-authors include Yi Mei, Mengjie Zhang, Wei–Neng Chen, Jun Zhang, Tianlong Gu, Huaqiang Yuan, Huaxiang Zhang, Bin Xin, Will N. Browne and Ying Lin. Their work appears in journals such as IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, IEEE Transactions on Systems Man and Cybernetics Systems, IEEE Transactions on Artificial Intelligence and Swarm and Evolutionary Computation.

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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