B. Cannas
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- Magnetic confinement fusion research 39
- Environmental Engineering top 5%
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- Chaos control and synchronization 15
- Water Science and Technology top 5%
- Signal Processing top 5%
- Time Series Analysis and Forecasting 13
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- Neural Networks and Applications 16
- Anomaly Detection Techniques and Applications 16
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- Nuclear reactor physics and engineering 10
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- Fusion materials and technologies 9
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- Network Security and Intrusion Detection 8
- Journals
- Nuclear Fusion (16 papers)Fusion Engineering and Design (11 papers)Plasma Physics and Controlled Fusion (7 papers)
- Partner nations
- ItalyGermanyUnited States
In The Last Decade
B. Cannas
102 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 101
- Nuclear and High Energy Physics 601
- Environmental Engineering 306
- Statistical and Nonlinear Physics 183
- Water Science and Technology 198
- Signal Processing 149
Countries citing papers authored by B. Cannas
This map shows the geographic impact of B. Cannas'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 B. Cannas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites B. Cannas more than expected).
Fields of papers citing papers by B. Cannas
This network shows the impact of papers produced by B. Cannas. 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 B. Cannas. The network helps show where B. Cannas may publish in the future.
Co-authorship network
The 25 scholars most cited alongside B. Cannas, 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 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 3 | |
| 5 | 2023 | 3 | |
| 6 | 2023 | 10 | |
| 7 | 2023 | 4 | |
| 8 | 2022 | 33 | |
| 9 | 2021 | 8 | |
| 10 | 2020 | 4 | |
| 11 | 2020 | 4 | |
| 12 | 2020 | 25 | |
| 13 | 2020 | 22 | |
| 14 | 2019 | 3 | |
| 15 | 2019 | 49 | |
| 16 | 2018 | 33 | |
| 17 | Dynamic Neural Networks for Prediction of Disruptions in Fusion Reactors (Tokamaks) | 2007 | 2 |
| 18 | River flow forecasting using neural networks and wavelet analysis | 2005 | 48 |
| 19 | Alternative Neural Network Models for the Rainfall-Runoff Process | 2002 | 1 |
| 20 | Dynamic neural networks for the water flow forecasting | 2000 | 3 |
About B. Cannas
B. Cannas is a scholar working on Nuclear and High Energy Physics, Signal Processing, Statistical and Nonlinear Physics, Artificial Intelligence and Space and Planetary Science, having authored 109 papers that have together received 1.6k indexed citations. Recurring topics across this work include Magnetic confinement fusion research (39 papers), Neural Networks and Applications (16 papers), Anomaly Detection Techniques and Applications (16 papers), Chaos control and synchronization (15 papers), Time Series Analysis and Forecasting (13 papers), Nuclear reactor physics and engineering (10 papers), Fusion materials and technologies (9 papers) and Network Security and Intrusion Detection (8 papers). The work is most often cited by research in Nuclear and High Energy Physics (601 citations), Environmental Engineering (306 citations), Statistical and Nonlinear Physics (183 citations), Water Science and Technology (198 citations) and Signal Processing (149 citations). B. Cannas has collaborated with scholars based in Italy, Germany and United States. Frequent co-authors include Alessandra Fanni, G. Sias, Silvano Cincotti, P. Sonato, Linda See, A. Murari, A. Pau, F. Pisano, G. Pautasso and Sara Carcangiu. Their work appears in journals such as Nuclear Fusion, Fusion Engineering and Design, Plasma Physics and Controlled Fusion, IEEE Transactions on Plasma Science and IEEE Transactions on Magnetics.
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.