Raphaël Nedellec
Impact in
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- Grey System Theory Applications
- Forecasting Techniques and Applications
- Stock Market Forecasting Methods
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- Energy Load and Power Forecasting
- Electric Power System Optimization
- Smart Grid Energy Management
Papers in
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- Grey System Theory Applications 2
- Forecasting Techniques and Applications 1
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- Energy Load and Power Forecasting 3
- Electric Power System Optimization 1
- Co-authors
- Yannig Goude (5 shared papers)Pierre Gaillard (1 shared paper)Matteo Fasiolo (2 shared papers)Simon N. Wood (2 shared papers)Jairo Cugliari (1 shared paper)Kay Mann (1 shared paper)Mark S. Pearce (1 shared paper)Adrian Rees (1 shared paper)
- Journals
- International Journal of Forecasting (2 papers)Journal of Statistical Software (1 paper)Journal of Computational and Graphical Statistics (1 paper)IEEE Transactions on Smart Grid (1 paper)PubMed (1 paper)
- Partner nations
- FranceUnited Kingdom
In The Last Decade
Raphaël Nedellec
6 papers receiving 547 citations
Peers
Comparison fields: 5 of 101
- Management Science and Operations Research 147
- Electrical and Electronic Engineering 347
- Ecological Modeling 14
- Artificial Intelligence 91
- Environmental Engineering 40
Countries citing papers authored by Raphaël Nedellec
This map shows the geographic impact of Raphaël Nedellec'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 Raphaël Nedellec with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphaël Nedellec more than expected).
Fields of papers citing papers by Raphaël Nedellec
This network shows the impact of papers produced by Raphaël Nedellec. 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 Raphaël Nedellec. The network helps show where Raphaël Nedellec may publish in the future.
Co-authors
The 9 scholars most cited alongside Raphaël Nedellec, 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 | 2014 | 162 | |
| 2 | 2016 | 150 | |
| 3 | 2019 | 132 | |
| 4 | 2013 | 60 | |
| 5 | 2021 | 51 | |
| 6 | 2013 | 2 |
About Raphaël Nedellec
Raphaël Nedellec is a scholar working on Management Science and Operations Research, Electrical and Electronic Engineering, Statistics and Probability, Computer Vision and Pattern Recognition and Signal Processing, having authored 6 papers that have together received 557 indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (3 papers), Statistical Methods and Bayesian Inference (2 papers), Grey System Theory Applications (2 papers), Statistical Methods and Inference (2 papers), Advanced Statistical Methods and Models (1 paper), Electric Power System Optimization (1 paper), Forecasting Techniques and Applications (1 paper) and Image and Signal Denoising Methods (1 paper). The work is most often cited by research in Management Science and Operations Research (147 citations), Electrical and Electronic Engineering (347 citations), Ecological Modeling (14 citations), Artificial Intelligence (91 citations) and Environmental Engineering (40 citations). Raphaël Nedellec has collaborated with scholars based in France and United Kingdom. Frequent co-authors include Yannig Goude, Pierre Gaillard, Matteo Fasiolo, Simon N. Wood, Jairo Cugliari, Kay Mann, Mark S. Pearce, Adrian Rees and Fiona Pearson. Their work appears in journals such as International Journal of Forecasting, Journal of Statistical Software, Journal of Computational and Graphical Statistics, IEEE Transactions on Smart Grid and PubMed.
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.