Konrad Świrski
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- Renewable energy and sustainable power systems 4
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- Advancements in Solid Oxide Fuel Cells 6
- Nuclear Materials and Properties 4
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- Fuel Cells and Related Materials 6
- Integrated Energy Systems Optimization 4
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- Advanced Control Systems Optimization 12
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- Artificial Immune Systems Applications 5
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- Nuclear reactor physics and engineering 4
Konrad Świrski
32 papers receiving 341 citations
Peers
Comparison fields: 5 of 55
- Renewable Energy, Sustainability and the Environment 77
- Catalysis 28
- Materials Chemistry 170
- Electrical and Electronic Engineering 201
- Energy Engineering and Power Technology 8
Countries citing papers authored by Konrad Świrski
This map shows the geographic impact of Konrad Świrski'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 Konrad Świrski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Konrad Świrski more than expected).
Fields of papers citing papers by Konrad Świrski
This network shows the impact of papers produced by Konrad Świrski. 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 Konrad Świrski. The network helps show where Konrad Świrski may publish in the future.
Co-authorship network
The 21 scholars most cited alongside Konrad Świrski, 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 | 2024 | 0 | |
| 2 | 2024 | 4 | |
| 3 | 2023 | 3 | |
| 4 | 2023 | 8 | |
| 5 | 2020 | 2 | |
| 6 | Long-term prediction of underground gas storage user gas flow nominations | 2020 | 1 |
| 7 | 2019 | 1 | |
| 8 | New approach to optimizing combustion in power boilers using software inspired by the immune system integrated with an in-furnace temperature monitoring system | 2018 | 1 |
| 9 | 2017 | 2 | |
| 10 | 2014 | 1 | |
| 11 | 2013 | 11 | |
| 12 | Artificial neural network as SOFC model | 2011 | 5 |
| 13 | Power Plant Performance Monitoring Using Statistical Methodology Approach | 2011 | 6 |
| 14 | Ways of enhancing operational efficiency at power and CHP plants | 2011 | 1 |
| 15 | 2010 | 2 | |
| 16 | Modeling of fuel composition influences on solid oxide fuel cell performance by artificial neural networks | 2009 | 2 |
| 17 | Sieci neuronowe w optymalizacji procesów energetycznych | 2009 | 0 |
| 18 | Maintaining Good Conditioning of Model Identification Task in Immune Inspired On-line Optimizer of an Industrial Process | 2009 | 1 |
| 19 | 2009 | 93 | |
| 20 | 2006 | 1 |
About Konrad Świrski
Konrad Świrski is a scholar working on Control and Systems Engineering, Renewable Energy, Sustainability and the Environment and Materials Chemistry, having authored 34 papers that have together received 356 indexed citations. Recurring topics across this work include Advanced Control Systems Optimization (12 papers), Advancements in Solid Oxide Fuel Cells (6 papers), Fuel Cells and Related Materials (6 papers), Artificial Immune Systems Applications (5 papers), Integrated Energy Systems Optimization (4 papers), Renewable energy and sustainable power systems (4 papers), Nuclear reactor physics and engineering (4 papers) and Nuclear Materials and Properties (4 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (77 citations), Catalysis (28 citations) and Materials Chemistry (170 citations). Konrad Świrski has collaborated with scholars based in Poland, France and Italy. Frequent co-authors include J. Milewski, Massimo Santarelli, Pierluigi Leone, Konrad Wojdan, Jakub Białek, Błażej Ruszczycki, Arkadiusz Szczęśniak, Olaf Dybiński, Michał Warchoł and Maciej Siekierski. Their work appears in journals such as Renewable and Sustainable Energy Reviews, International Journal of Hydrogen Energy and Energy.
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.