Brian Carse

36 papers receiving 371 citations

Peers

Brian Carse
Comparison fields: 5 of 60
  • Artificial Intelligence 312
  • Control and Systems Engineering 73
  • Electrical and Electronic Engineering 31
  • Computer Vision and Pattern Recognition 30
  • Computational Theory and Mathematics 28
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Citations per field
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Citations per year

Countries citing papers authored by Brian Carse

Since Specialization
Citations

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

Fields of papers citing papers by Brian Carse

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brian Carse

This figure shows the co-authorship network connecting the top 25 collaborators of Brian Carse. A scholar is included among the top collaborators of Brian Carse 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 Brian Carse. Brian Carse 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
#WorkIndexed citations
1 8
2 3
3 9
4 2
5 12
6
Fault diagnosis of power distribution systems using a multi-agent approach
3
7
Current issues and future directions in evolutionary fuzzy systems research.
1
8
Fuzzy logic and the Pittsburgh classifier system for mobile robot control.
0
9 1
10 2
11 3
12
X-FCS: a fuzzy classifier system using accuracy based fitness - first results.
5
13
Solution of Inverse Problems in Laser Spectroscopy of Water Media with the Help of Neural Networks
0
14
A Framework for Evolving Fuzzy Classifier Systems Using Genetic Programming
3
15
Michigan and Pittsburgh Fuzzy Classifier Systems for Learning Mobile Robot Control Rules: An Experimental Comparison
1
16
Autonomous acquisition of fuzzy rules for mobile robot control: first results from two evolutionary computation approaches
7
17
A note on learning and evolution in neural networks
1
18 166
19
Evolving multi-agent systems
5
20 4

About Brian Carse

Brian Carse is a scholar working on Artificial Intelligence, Control and Systems Engineering and Human-Computer Interaction, having authored 39 papers that have together received 392 indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (21 papers), Fuzzy Logic and Control Systems (20 papers) and Metaheuristic Optimization Algorithms Research (16 papers). The work is most often cited by research in Artificial Intelligence (312 citations), Control and Systems Engineering (73 citations) and Management Science and Operations Research (25 citations). Brian Carse has collaborated with scholars based in United Kingdom, Sweden and Spain. Frequent co-authors include Terence C. Fogarty, Alistair Munro, Jorge Casillas, Tony Pipe, Larry Bull, Hassan Nouri, Tim Hill, Zdravko Markov, Paul Bremner and Ingrid Russell. Their work appears in journals such as The Journal of Experimental Medicine, IEEE Transactions on Fuzzy Systems and Fuzzy Sets and Systems.

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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