Jianzhou Wang

15.9k total citations · 1 hit paper
278 papers, 12.8k citations indexed

About

Jianzhou Wang is a scholar working on Electrical and Electronic Engineering, Management Science and Operations Research and Artificial Intelligence. According to data from OpenAlex, Jianzhou Wang has authored 278 papers receiving a total of 12.8k indexed citations (citations by other indexed papers that have themselves been cited), including 176 papers in Electrical and Electronic Engineering, 113 papers in Management Science and Operations Research and 76 papers in Artificial Intelligence. Recurrent topics in Jianzhou Wang's work include Energy Load and Power Forecasting (175 papers), Grey System Theory Applications (78 papers) and Electric Power System Optimization (73 papers). Jianzhou Wang is often cited by papers focused on Energy Load and Power Forecasting (175 papers), Grey System Theory Applications (78 papers) and Electric Power System Optimization (73 papers). Jianzhou Wang collaborates with scholars based in China, Macao and Australia. Jianzhou Wang's co-authors include Wendong Yang, Haiyan Lu, Tong Niu, Pei Du, Xinsong Niu, Zhenkun Liu, Lifang Zhang, Zhiwu Li, Hongmin Li and Zhe George Zhang and has published in prestigious journals such as Nature, Nature Genetics and Applied Physics Letters.

In The Last Decade

Jianzhou Wang

274 papers receiving 12.5k citations

Hit Papers

Forecasting stock indices with back propagation neural ne... 2011 2026 2016 2021 2011 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jianzhou Wang China 63 7.0k 3.4k 3.0k 2.3k 1.3k 278 12.8k
Hui Liu China 57 6.2k 0.9× 1.5k 0.4× 3.0k 1.0× 1.9k 0.8× 339 0.3× 531 12.4k
Henrik Madsen Denmark 63 9.0k 1.3× 825 0.2× 2.3k 0.8× 2.1k 0.9× 518 0.4× 564 16.9k
Jianzhou Wang China 50 5.7k 0.8× 2.2k 0.6× 2.2k 0.7× 1.2k 0.5× 497 0.4× 132 7.7k
Shahaboddin Shamshirband Iran 75 4.1k 0.6× 685 0.2× 4.4k 1.4× 3.5k 1.5× 212 0.2× 327 17.1k
Zong Woo Geem South Korea 48 3.1k 0.4× 742 0.2× 6.5k 2.2× 913 0.4× 177 0.1× 254 17.0k
Shanlin Yang China 57 3.8k 0.5× 2.2k 0.6× 2.5k 0.8× 959 0.4× 1.5k 1.2× 351 12.1k
Wenfeng Zheng China 64 1.2k 0.2× 280 0.1× 2.5k 0.8× 1.1k 0.5× 510 0.4× 220 9.9k
Sancho Salcedo‐Sanz Spain 50 3.6k 0.5× 565 0.2× 3.5k 1.2× 1.4k 0.6× 157 0.1× 371 9.5k
Andrew Lewis Australia 25 6.8k 1.0× 1.0k 0.3× 13.1k 4.3× 826 0.4× 222 0.2× 114 28.4k
Tianrui Li China 67 1.3k 0.2× 2.1k 0.6× 7.3k 2.4× 962 0.4× 138 0.1× 767 17.7k

Countries citing papers authored by Jianzhou Wang

Since Specialization
Citations

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

Fields of papers citing papers by Jianzhou Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jianzhou Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Jianzhou Wang. A scholar is included among the top collaborators of Jianzhou Wang 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 Jianzhou Wang. Jianzhou Wang 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
1.
Li, Hengyun, et al.. (2025). Tourism combination forecasting with swarm intelligence. Annals of Tourism Research. 111. 103932–103932. 2 indexed citations
2.
Ma, Fang, Zhe Liu, Jianzhou Wang, et al.. (2025). N6-methyladenosine RNA methylation regulates microplastics-induced cell senescence in the rainbow trout liver. The Science of The Total Environment. 961. 178363–178363.
3.
Wang, Jianzhou, et al.. (2025). Using explainable deep learning to improve decision quality: Evidence from carbon trading market. Omega. 133. 103281–103281. 1 indexed citations
4.
5.
Zhang, Hao, et al.. (2025). A new perspective on non-ferrous metal price forecasting: An interpretable two-stage ensemble learning-based interval-valued forecasting system. Advanced Engineering Informatics. 65. 103267–103267. 2 indexed citations
6.
Wang, Jianzhou, et al.. (2025). A multi-input and three-output wind speed point-interval prediction system based on constrained many-objective optimization problem. Information Sciences. 720. 122531–122531. 1 indexed citations
7.
Wang, Jianzhou, et al.. (2024). Solar photovoltaic power forecasting system with online manner based on adaptive mode decomposition and multi-objective optimization. Computers & Electrical Engineering. 118. 109407–109407. 8 indexed citations
8.
Zeng, Bo, et al.. (2024). A novel structure grey prediction model with strong compatibility and its application in forecasting the annual average concentration of particulate matter in Beijing. Engineering Applications of Artificial Intelligence. 136. 108974–108974. 2 indexed citations
9.
Yu, Qi, et al.. (2024). A paradigm shift in solar energy forecasting: A novel two-phase model for monthly residential consumption. Energy. 305. 132192–132192. 6 indexed citations
10.
Wang, Jianzhou, et al.. (2024). A multi-input and dual-output wind speed interval forecasting system based on constrained multi-objective optimization problem and model averaging. Energy Conversion and Management. 319. 118909–118909. 10 indexed citations
11.
Wang, Jianzhou, et al.. (2024). Particulate Matter 2.5 concentration prediction system based on uncertainty analysis and multi-model integration. The Science of The Total Environment. 958. 177924–177924.
13.
Liu, Zhenkun, Ping Jiang, Koen W. De Bock, et al.. (2023). Extreme gradient boosting trees with efficient Bayesian optimization for profit-driven customer churn prediction. Technological Forecasting and Social Change. 198. 122945–122945. 46 indexed citations
14.
Wang, Jianzhou, et al.. (2023). An integrated system to significant wave height prediction: Combining feature engineering, multi-criteria decision making, and hybrid kernel density estimation. Expert Systems with Applications. 241. 122351–122351. 11 indexed citations
15.
Zhang, Ziyuan, et al.. (2023). A novel ensemble system for short-term wind speed forecasting based on Two-stage Attention-Based Recurrent Neural Network. Renewable Energy. 204. 11–23. 69 indexed citations
16.
Sun, Yuhuan, et al.. (2023). Combined forecasting tool for renewable energy management in sustainable supply chains. Computers & Industrial Engineering. 179. 109237–109237. 36 indexed citations
17.
Wang, Jianzhou, et al.. (2023). Enhancing investment performance of Black-Litterman model with AI hybrid system: Can it be done?. Expert Systems with Applications. 244. 122924–122924. 6 indexed citations
18.
Liu, Zhenkun, et al.. (2023). Interval forecasting for wind speed using a combination model based on multiobjective artificial hummingbird algorithm. Applied Soft Computing. 150. 111090–111090. 29 indexed citations
20.
Wang, Xinyu, Jianzhou Wang, Xinsong Niu, & C.L. Wu. (2023). Novel wind-speed prediction system based on dimensionality reduction and nonlinear weighting strategy for point-interval prediction. Expert Systems with Applications. 241. 122477–122477. 21 indexed citations

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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