Guangbo Li

518 citations
4 papers · 444 · 1 hit paper · h-index 3

Impact in

Papers in

Guangbo Li

4 papers receiving 439 citations

Guangbo Li's Hit Papers

Deep belief network based deterministic and probabilistic wind speed forecasting approach 2016 · 431 citations
4310+3+6Years since publication100200300400

Peers

Guangbo Li
Comparison fields: 5 of 66
  • Energy Engineering and Power Technology 29
  • Electrical and Electronic Engineering 332
  • Management Science and Operations Research 66
  • Artificial Intelligence 150
  • Environmental Engineering 48
Replace J.-C. Peng with:
J.-C. Peng China
Zhewen Niu China
Danxiang Wei Macao
Shahram Hanifi United Kingdom
K U Jaseena India
Mucun Sun United States
Yunxuan Dong China
Zhirui Tian China
Chunlei Ji China
Guangbo Li relative to J.-C. Peng China J.-C. Peng's profile →
Citations per field
00.5×1.5×
J.-C. Peng · 1×
Citations per year

Countries citing papers authored by Guangbo Li

Since Specialization
Citations

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

Fields of papers citing papers by Guangbo Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside Guangbo Li, 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 Guangbo Li Line = papers co-authored together Guangbo Li links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown
#Work
1
Deep belief network based deterministic and probabilistic wind speed forecasting approach
Hit paper breakdown →
2016431
2 20248
3 20243
4 20242

About Guangbo Li

Guangbo Li is a scholar working on Organic Chemistry, Automotive Engineering, Aquatic Science, Ecology and Health, Toxicology and Mutagenesis, having authored 4 papers that have together received 444 indexed citations. Recurring topics across this work include Isotope Analysis in Ecology (1 paper), Nitric Oxide and Endothelin Effects (1 paper), Nanomaterials for catalytic reactions (1 paper), Marine Bivalve and Aquaculture Studies (1 paper), Catalytic Processes in Materials Science (1 paper), Air Quality Monitoring and Forecasting (1 paper), Air Quality and Health Impacts (1 paper) and Vehicle emissions and performance (1 paper). The work is most often cited by research in Energy Engineering and Power Technology (29 citations), Electrical and Electronic Engineering (332 citations), Management Science and Operations Research (66 citations), Artificial Intelligence (150 citations) and Environmental Engineering (48 citations). Guangbo Li has collaborated with scholars based in Hong Kong and China. Frequent co-authors include J.-C. Peng, Yitao Liu, Hai‐Kun Wang, Qixing Ji, Kehua Chen, Qingyi Liu, Hong‐Cheng Wang, Wenfang Lin, Yuqi Wang and Wenzhe Wang. Their work appears in journals such as Water Research X, Applied Energy, Environmental Research and Journal of Geophysical Research Biogeosciences.

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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