Ya Liu

1.1k citations
46 papers · 721 · h-index 12

Impact in

Papers in

Ya Liu

37 papers receiving 689 citations

Peers

Ya Liu
Comparison fields: 5 of 118
  • Industrial and Manufacturing Engineering 189
  • Applied Psychology 60
  • Clinical Psychology 200
  • Social Psychology 174
  • Mechanical Engineering 224
Replace Matthias G. Arend with:
Matthias G. Arend Germany
Koen Smit Netherlands
Alejandro Ramos Martín Spain
Wenshu Luo Singapore
Minsun Lee South Korea
Yunan Chen United States
Qiming Huang China
Mohammad Mehdi Khabiri Iran
Ya Liu relative to Matthias G. Arend Germany Matthias G. Arend's profile →
Citations per field
00.5×10×15×20×23.6×
Matthias G. Arend · 1×
Citations per year

Countries citing papers authored by Ya Liu

Since Specialization
Citations

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

Fields of papers citing papers by Ya Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013160
2 2014131
3 201976
4 201761
5 202132
6 202030
7 201928
8 202026
9 201823
10 202022
11 202121
12 202411
13 20129
14 20208
15 20227
16 20226
17
Forecast of gas line status at real time based on modified Elman neural network
20035
18 20105
19 20165
20 20205

About Ya Liu

Ya Liu is a scholar working on Artificial Intelligence, Mechanical Engineering, Industrial and Manufacturing Engineering, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 46 papers that have together received 721 indexed citations. Recurring topics across this work include Recycling and Waste Management Techniques (10 papers), Extraction and Separation Processes (10 papers), Cryptographic Implementations and Security (8 papers), Chaos-based Image/Signal Encryption (8 papers), Coding theory and cryptography (5 papers), Advancements in Battery Materials (3 papers), Advanced Frequency and Time Standards (3 papers) and GNSS positioning and interference (2 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (189 citations), Applied Psychology (60 citations), Clinical Psychology (200 citations), Social Psychology (174 citations) and Mechanical Engineering (224 citations). Ya Liu has collaborated with scholars based in China, Belgium and United States. Frequent co-authors include Zhenhong Wang, Qingming Song, Lingen Zhang, Wei Lü, Zhenming Xu, Zhenming Xu, Ruitong Gao, Dawu Gu, Wei Li and Zhiqiang Liu. Their work appears in journals such as Journal of Cleaner Production, Journal of Hazardous Materials, The Computer Journal, Personality and Individual Differences and Computer Networks.

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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