Tomas Landelius

1.4k total citations
43 papers, 985 citations indexed

About

Tomas Landelius is a scholar working on Artificial Intelligence, Atmospheric Science and Global and Planetary Change. According to data from OpenAlex, Tomas Landelius has authored 43 papers receiving a total of 985 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 17 papers in Atmospheric Science and 12 papers in Global and Planetary Change. Recurrent topics in Tomas Landelius's work include Solar Radiation and Photovoltaics (11 papers), Meteorological Phenomena and Simulations (11 papers) and Neural Networks and Applications (8 papers). Tomas Landelius is often cited by papers focused on Solar Radiation and Photovoltaics (11 papers), Meteorological Phenomena and Simulations (11 papers) and Neural Networks and Applications (8 papers). Tomas Landelius collaborates with scholars based in Sweden, United Kingdom and Spain. Tomas Landelius's co-authors include Hans Knutsson, Weine Josefsson, Magnus Borga, Birgit Koehler, Lars J. Tranvik, Per Dahlgren, Stefan Gollvik, Gesa A. Weyhenmeyer, Pietro Elia Campana and Sandra Andersson and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Water Research and Journal of Cleaner Production.

In The Last Decade

Tomas Landelius

41 papers receiving 920 citations

Peers

Tomas Landelius
Comparison fields: 5 of 101
  • Global and Planetary Change 327
  • Atmospheric Science 308
  • Artificial Intelligence 218
  • Oceanography 156
  • Electrical and Electronic Engineering 103
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Citations per field, relative to Tomas Landelius
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Citations per year, relative to Tomas Landelius
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Countries citing papers authored by Tomas Landelius

Since Specialization
Citations

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

Fields of papers citing papers by Tomas Landelius

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomas Landelius

This figure shows the co-authorship network connecting the top 25 collaborators of Tomas Landelius. A scholar is included among the top collaborators of Tomas Landelius 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 Tomas Landelius. Tomas Landelius 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
# Work Indexed citations
1 8
2 25
3 23
4
Using artificial intelligence for the water-food-energy nexus management during drought in Sweden
3
5 24
6 0
7 60
8 54
9 130
10 1
11 2
12
A system for modelling solar radiation parameters with mesoscale spatial resolution
19
13
Learning Canonical Correlations
15
14 1
15 2
16
Greedy adaptive critics for LPQ [dvs LQR] problems : Convergence Proofs
2
17
Reinforcement Learning Adaptive Control and Explicit Criterion Maximization
2
18
On-Line Singular Value Decomposition of Stochastic Process Covariances
3
19
Behavior Representation by Growing a Learning Tree
8
20
The Learning Tree, A New Concept in Learning
3

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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