Ling Yang

1.1k citations
50 papers · 818 indexed · 1 hit paper · h-index 15
Topics
Machine Learning and ELM (10 papers)Advanced Statistical Process Monitoring (8 papers)Spectroscopy and Chemometric Analyses (8 papers)
Partner nations
ChinaTaiwanUnited States

In The Last Decade

Ling Yang

46 papers receiving 786 citations

Hit Papers

DSTP-RNN: A dual-stage two-phase attention-based recurren...2019202620212023201950100150200250

Peers

Ling Yang
Comparison fields: 5 of 120
  • Artificial Intelligence 129
  • Analytical Chemistry 104
  • Computer Vision and Pattern Recognition 100
  • Management Science and Operations Research 98
  • Water Science and Technology 98
Replace Ferenc Szeifert with:
Ferenc Szeifert Hungary
Federico Castanedo Spain
Ratko Grbić Croatia
Jun Liang China
Q. Peter He United States
Rajendra Kumar Sharma India
Melanie Po‐Leen Ooi Malaysia
Yuehua Liu China
Di Wang China
Ling Yang relative to Ferenc Szeifert Hungary Ferenc Szeifert's profile →
Citations per field
00.5×10×15.3×
Ferenc Szeifert · 1×
Citations per year

Countries citing papers authored by Ling Yang

Since Specialization
Citations

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

Fields of papers citing papers by Ling Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ling Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Ling Yang. A scholar is included among the top collaborators of Ling Yang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ling Yang. Ling Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 0
3 1
4 1
5 1
6 0
7 19
8 1
9
DSTP-RNN: A dual-stage two-phase attention-based recurrent neural network for long-term and multivariate time series predictionbreakdown →
271
10 18
11 4
12 5
13 2
14 0
15 6
16 6
17
A Novel CUSUM Median Control Chart
11
18 2
19 6
20 0

About Ling Yang

Ling Yang is a scholar working on Medical Laboratory Technology, Statistics, Probability and Uncertainty and Analytical Chemistry, having authored 50 papers that have together received 818 indexed citations. Recurring topics across this work include Machine Learning and ELM (10 papers), Advanced Statistical Process Monitoring (8 papers) and Spectroscopy and Chemometric Analyses (8 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (96 citations), Analytical Chemistry (104 citations) and Signal Processing (94 citations). Ling Yang has collaborated with scholars based in China, Taiwan and United States. Frequent co-authors include Yingyi Chen, Yeqi Liu, Chuanyang Gong, Shey‐Huei Sheu, Ting Wu, Zhi Li, Pan Zhang, Huihui Yu, Daoliang Li and Wei‐Hung Lin. Their work appears in journals such as PLoS ONE, Expert Systems with Applications and Aquaculture.

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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