Mayur Barman
Impact in
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- Grey System Theory Applications
- Stock Market Forecasting Methods
Papers in
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- Energy Load and Power Forecasting 5
- Electric Power System Optimization 2
- Smart Grid Energy Management 2
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- Grey System Theory Applications 2
- Stock Market Forecasting Methods 2
- Forecasting Techniques and Applications 1
- Co-authors
- Nalin Behari Dev Choudhury (5 shared papers)Sadhan Mahapatra (1 shared paper)Debajit Palit (1 shared paper)Durgesh Nandan (1 shared paper)
- Journals
- Energy (2 papers)Energy Sustainable Development (1 paper)Sustainable Cities and Society (1 paper)International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (1 paper)Procedia Computer Science (1 paper)
- Partner nations
- India
In The Last Decade
Mayur Barman
7 papers receiving 417 citations
Peers
Comparison fields: 5 of 54
- Energy Engineering and Power Technology 32
- Management Science and Operations Research 124
- Electrical and Electronic Engineering 334
- Business and International Management 11
- Pollution 53
Countries citing papers authored by Mayur Barman
This map shows the geographic impact of Mayur Barman'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 Mayur Barman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mayur Barman more than expected).
Fields of papers citing papers by Mayur Barman
This network shows the impact of papers produced by Mayur Barman. 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 Mayur Barman. The network helps show where Mayur Barman may publish in the future.
Co-authors
The 4 scholars most cited alongside Mayur Barman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 194 | |
| 2 | 2019 | 95 | |
| 3 | 2017 | 59 | |
| 4 | 2020 | 58 | |
| 5 | 2018 | 17 | |
| 6 | A fuzzy logic controller based mid-term load forecasting with renewable penetration in Assam, India | 2017 | 2 |
| 7 | 2022 | 1 |
About Mayur Barman
Mayur Barman is a scholar working on Electrical and Electronic Engineering, Management Science and Operations Research, Environmental Engineering, Pollution and Control and Systems Engineering, having authored 7 papers that have together received 426 indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (5 papers), Hydrological Forecasting Using AI (2 papers), Electric Power System Optimization (2 papers), Grey System Theory Applications (2 papers), Smart Grid Energy Management (2 papers), Stock Market Forecasting Methods (2 papers), Microgrid Control and Optimization (1 paper) and Forecasting Techniques and Applications (1 paper). The work is most often cited by research in Energy Engineering and Power Technology (32 citations), Management Science and Operations Research (124 citations), Electrical and Electronic Engineering (334 citations), Business and International Management (11 citations) and Pollution (53 citations). Mayur Barman has collaborated with scholars based in India. Frequent co-authors include Nalin Behari Dev Choudhury, Sadhan Mahapatra, Debajit Palit and Durgesh Nandan. Their work appears in journals such as Energy, Energy Sustainable Development, Sustainable Cities and Society, International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering and Procedia Computer Science.
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.