Liting Zhang

41 papers receiving 472 citations

Liting Zhang's Hit Papers

A comparative study of 11 non-linear regression models highlighting autoencoder, DBN, and SVR, enhanced by SHAP importance analysis in soybean branching prediction 2024 · 56 citations
560+1Years since publication1020304050

Peers

Liting Zhang
Comparison fields: 5 of 116
  • Insect Science 63
  • Food Science 62
  • Plant Science 117
  • Management, Monitoring, Policy and Law 32
  • Hepatology 21
Replace Xiaoqing Wei with:
Xiaoqing Wei China
Jae‐Joon Lee South Korea
Yaoxiang Li United States
Jiaqi Hao China
Zhongrong Zhang China
Chun Wang China
Xuezhen Li China
Jiong Liu China
Doudou Li China
Liting Zhang relative to Xiaoqing Wei China Xiaoqing Wei's profile →
Citations per field
00.5×6.4×
Xiaoqing Wei · 1×
Citations per year

Countries citing papers authored by Liting Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Liting Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201976
2
A comparative study of 11 non-linear regression models highlighting autoencoder, DBN, and SVR, enhanced by SHAP importance analysis in soybean branching prediction
Hit paper breakdown →
202456
3 201946
4 201836
5 202328
6 202226
7 201824
8 202422
9 202221
10 202217
11 202214
12 201713
13 202213
14 202112
15 20228
16 20187
17 20246
18 20216
19 20236
20 20224

About Liting Zhang

Liting Zhang is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology, Cognitive Neuroscience, Plant Science and Epidemiology, having authored 51 papers that have together received 479 indexed citations. Recurring topics across this work include ECG Monitoring and Analysis (10 papers), EEG and Brain-Computer Interfaces (7 papers), Liver Disease Diagnosis and Treatment (4 papers), Dam Engineering and Safety (4 papers), Liver physiology and pathology (3 papers), Landslides and related hazards (3 papers), Non-Invasive Vital Sign Monitoring (3 papers) and Essential Oils and Antimicrobial Activity (3 papers). The work is most often cited by research in Insect Science (63 citations), Food Science (62 citations), Plant Science (117 citations), Management, Monitoring, Policy and Law (32 citations) and Hepatology (21 citations). Liting Zhang has collaborated with scholars based in China, United States and Indonesia. Frequent co-authors include Zhu‐Feng Geng, Yi-Xi Feng, Shu-Shan Du, Xue Pang, Shanshan Guo, Chao Xi, Li Wang, Di Zhang, Ziyi Zhang and Shoushui Wei. Their work appears in journals such as Environmental Science and Pollution Research, Biomedical Signal Processing and Control, Frontiers in Cardiovascular Medicine, Alexandria Engineering Journal and Scientific Reports.

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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