Hongda Liu

82 papers receiving 1.9k citations

Hongda Liu's Hit Papers

Photovoltaic power forecasting based LSTM-Convolutional Network 2019 · 378 citations
3780+2+4Years since publication100200300400

Peers

Hongda Liu
Comparison fields: 5 of 109
  • Energy Engineering and Power Technology 113
  • Renewable Energy, Sustainability and the Environment 464
  • Artificial Intelligence 725
  • Electrical and Electronic Engineering 1.0k
  • Management Science and Operations Research 126
Replace Cong Feng with:
Cong Feng China
Yitao Liu China
Francisco Javier Martínez-de-Pisón Spain
Dipankar Deb India
A. Immanuel Selvakumar India
Yang Du China
Qi Liao China
Jinliang Zhang China
Muhammed A. Hassan Egypt
Soma Shekara Sreenadh Reddy Depuru United States
Hongda Liu relative to Cong Feng China Cong Feng's profile →
Citations per field
00.5×1.6×
Cong Feng · 1×
Citations per year

Countries citing papers authored by Hongda Liu

Since Specialization
Citations

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

Fields of papers citing papers by Hongda Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 86 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A comparison of day-ahead photovoltaic power forecasting models based on deep learning neural network
Hit paper breakdown →
2019430
2
Photovoltaic power forecasting based LSTM-Convolutional Network
Hit paper breakdown →
2019378
3 2018253
4 202071
5 201671
6 201961
7 201754
8 201749
9 201746
10 201329
11 202128
12 201825
13 202325
14 202020
15 202519
16 200716
17 202315
18 201714
19 201514
20 201914

About Hongda Liu

Hongda Liu is a scholar working on Electrical and Electronic Engineering, Control and Systems Engineering, Mechanical Engineering, Energy Engineering and Power Technology and Computational Mechanics, having authored 86 papers that have together received 1.9k indexed citations. Recurring topics across this work include Microgrid Control and Optimization (9 papers), Advanced machining processes and optimization (9 papers), Power Systems and Renewable Energy (8 papers), Maritime Transport Emissions and Efficiency (7 papers), Advanced Algorithms and Applications (6 papers), Smart Grid and Power Systems (6 papers), Hybrid Renewable Energy Systems (6 papers) and Advanced Machining and Optimization Techniques (6 papers). The work is most often cited by research in Energy Engineering and Power Technology (113 citations), Renewable Energy, Sustainability and the Environment (464 citations), Artificial Intelligence (725 citations), Electrical and Electronic Engineering (1.0k citations) and Management Science and Operations Research (126 citations). Hongda Liu has collaborated with scholars based in China, Taiwan and United Kingdom. Frequent co-authors include Xiaoxia Qi, Kejun Wang, Hongguang Zhang, Fubin Yang, Feiqi Deng, Wenxiong Kang, Lu Fang, Xiaochen Hou, Fei Yu and Jingfu Wang. Their work appears in journals such as Energies, Energy, Applied Energy, The International Journal of Advanced Manufacturing Technology and Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture.

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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