Yingyi Chen

149 papers receiving 3.3k citations

Yingyi Chen's Hit Papers

A Review of the Artificial Neural Network Models for Water Quality Prediction 2020 · 319 citations
3190+2+4Years since publication100200300

Peers

Yingyi Chen
Comparison fields: 5 of 174
  • Water Science and Technology 983
  • Environmental Engineering 602
  • Industrial and Manufacturing Engineering 264
  • Sensory Systems 84
  • Nature and Landscape Conservation 193
Replace Corrado Costa with:
Corrado Costa Italy
Min Zuo China
Paolo Menesatti Italy
Feng China
Daniel L. Villeneuve United States
Douglas R. Smith United States
Seyed Saeid Mohtasebi Iran
Francesca Antonucci Italy
Mikko Kolehmainen Finland
Lorena Parra Spain
Yingyi Chen relative to Corrado Costa Italy Corrado Costa's profile →
Citations per field
00.5×2.7×
Corrado Costa · 1×
Citations per year

Countries citing papers authored by Yingyi Chen

Since Specialization
Citations

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

Fields of papers citing papers by Yingyi Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 157 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Review of the Artificial Neural Network Models for Water Quality Prediction
Hit paper breakdown →
2020319
2
DSTP-RNN: A dual-stage two-phase attention-based recurrent neural network for long-term and multivariate time series prediction
Hit paper breakdown →
2019283
3 2020186
4 2020147
5 2016135
6 2016129
7 2019120
8 201387
9 202080
10 201575
11 202175
12 201672
13 201758
14 201955
15 202152
16 201651
17 202349
18 202047
19 201145
20 202341

About Yingyi Chen

Yingyi Chen is a scholar working on Water Science and Technology, Computer Vision and Pattern Recognition, Artificial Intelligence, Plant Science and Industrial and Manufacturing Engineering, having authored 157 papers that have together received 3.4k indexed citations. Recurring topics across this work include Water Quality Monitoring Technologies (40 papers), Water Quality Monitoring and Analysis (15 papers), Smart Agriculture and AI (13 papers), Fish Ecology and Management Studies (10 papers), Soil and Land Suitability Analysis (10 papers), Face and Expression Recognition (8 papers), Machine Learning and ELM (8 papers) and Remote-Sensing Image Classification (8 papers). The work is most often cited by research in Water Science and Technology (983 citations), Environmental Engineering (602 citations), Industrial and Manufacturing Engineering (264 citations), Sensory Systems (84 citations) and Nature and Landscape Conservation (193 citations). Yingyi Chen has collaborated with scholars based in China, Taiwan and United Kingdom. Frequent co-authors include Daoliang Li, Yeqi Liu, Huihui Yu, Lihua Song, Chuanyang Gong, Ling Yang, Ling Yang, Qian Zhang, Xiaomin Fang and Jian Zhang. Their work appears in journals such as Computers and Electronics in Agriculture, Engineering Applications of Artificial Intelligence, Applied Sciences, New Zealand Journal of Agricultural Research and Sensors.

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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