Yeqi Liu

2.3k citations
46 papers · 1.7k indexed · 2 hit papers · h-index 19

Yeqi Liu

43 papers receiving 1.6k citations

Hit Papers

A Review of the Artificial Neural Network Models for Wate...3002019202620212023100200300

Peers

Yeqi Liu
Comparison fields: 5 of 144
  • Water Science and Technology 457
  • Environmental Engineering 313
  • Industrial and Manufacturing Engineering 127
  • Radiation 81
  • Signal Processing 85
Replace Mehdi Bahrami with:
Mehdi Bahrami Iran
Manmohan Singh India
Tao Shen China
Jingjie Zhang China
Guoning Chen United States
Lei Lei China
Juntao Liu China
K. S. Rajan India
Jinglin Zhang China
Shihu Liu China
Yeqi Liu relative to Mehdi Bahrami Iran Mehdi Bahrami's profile →
Citations per field
00.5×6.2×
Mehdi Bahrami · 1×
Citations per year

Countries citing papers authored by Yeqi Liu

Since Specialization
Citations

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

Fields of papers citing papers by Yeqi Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20252
2 20257
3 20247
4 202427
5 20248
6 20241
7 202427
8 20242
9 20241
10 202324
11 202311
12 202322
13 20223
14 202230
15 202150
16 20202
17
A Review of the Artificial Neural Network Models for Water Quality Predictionbreakdown →
2020300
18
DSTP-RNN: A dual-stage two-phase attention-based recurrent neural network for long-term and multivariate time series predictionbreakdown →
2019271
19 2019115
20 20081

About Yeqi Liu

Yeqi Liu is a scholar working on Water Science and Technology, Industrial and Manufacturing Engineering and Molecular Medicine, having authored 46 papers that have together received 1.7k indexed citations. Recurring topics across this work include Perovskite Materials and Applications (11 papers), Luminescence Properties of Advanced Materials (8 papers), Water Quality Monitoring Technologies (8 papers), Organic Light-Emitting Diodes Research (5 papers), Fish Ecology and Management Studies (4 papers), Digital Radiography and Breast Imaging (4 papers), Satellite Communication Systems (4 papers) and Luminescence and Fluorescent Materials (4 papers). The work is most often cited by research in Water Science and Technology (457 citations), Environmental Engineering (313 citations) and Industrial and Manufacturing Engineering (127 citations). Yeqi Liu has collaborated with scholars based in China, United States and Malaysia. Frequent co-authors include Yingyi Chen, Lihua Song, Chuanyang Gong, Ling Yang, Daoliang Li, Ling Yang, Huihui Yu, Yuhai Zhang, Qian Zhang and Xiaojia Wang. Their work appears in journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and ACS Nano.

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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