Lean Yu

11.4k citations
216 papers · 8.1k · 2 hit papers · h-index 50

Impact in

Papers in

Lean Yu

211 papers receiving 7.8k citations

Lean Yu's Hit Papers

A deep learning ensemble approach for crude oil price forecasting 2017 · 289 citations
2890+6+12Years since publication100200300400500

Peers

Lean Yu
Comparison fields: 5 of 167
  • Management Science and Operations Research 2.9k
  • Economics and Econometrics 3.0k
  • General Energy 79
  • Accounting 774
  • Finance 595
Replace Kin Keung Lai with:
Kin Keung Lai Hong Kong
Ling Tang China
Michael Doumpos Greece
Desheng Wu China
Constantin Zopounidis Greece
Salvatore Greco Italy
Fenghua Wen China
Shanlin Yang China
Ruey S. Tsay United States
José Rui Figueira Portugal
Lean Yu relative to Kin Keung Lai Hong Kong Kin Keung Lai's profile →
Citations per field
00.5×2.6×
Kin Keung Lai · 1×
Citations per year

Countries citing papers authored by Lean Yu

Since Specialization
Citations

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

Fields of papers citing papers by Lean Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 216 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm
Hit paper breakdown →
2008578
2
A deep learning ensemble approach for crude oil price forecasting
Hit paper breakdown →
2017289
3 2010228
4 2009210
5 2015207
6 2004187
7 2015183
8 2018175
9 2015169
10 2008167
11 2012156
12 2008149
13 2007144
14 2019134
15 2012126
16 2017125
17 2018125
18 2009119
19 2014116
20 2017116

About Lean Yu

Lean Yu is a scholar working on Management Science and Operations Research, Artificial Intelligence, Economics and Econometrics, Electrical and Electronic Engineering and Accounting, having authored 216 papers that have together received 8.1k indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (47 papers), Imbalanced Data Classification Techniques (42 papers), Market Dynamics and Volatility (41 papers), Financial Distress and Bankruptcy Prediction (39 papers), Stock Market Forecasting Methods (39 papers), Grey System Theory Applications (24 papers), Multi-Criteria Decision Making (14 papers) and Forecasting Techniques and Applications (14 papers). The work is most often cited by research in Management Science and Operations Research (2.9k citations), Economics and Econometrics (3.0k citations), General Energy (79 citations), Accounting (774 citations) and Finance (595 citations). Lean Yu has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Kin Keung Lai, Shouyang Wang, Ling Tang, Jianping Li, Wei Dai, Kaijian He, Jiaqian Wu, Qin Bao, Rongda Chen and Xiang Li. Their work appears in journals such as International Journal of Information Technology & Decision Making, Expert Systems with Applications, Applied Soft Computing, Information Sciences and Energy Economics.

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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