Philippe Collard

627 citations
11 papers · 157 · h-index 7

Impact in

Papers in

Philippe Collard

10 papers receiving 145 citations

Peers

Philippe Collard
Comparison fields: 5 of 38
  • Artificial Intelligence 131
  • Computational Theory and Mathematics 63
  • Genetics 24
  • Industrial and Manufacturing Engineering 4
  • Molecular Biology 23
Replace Manuel Clergue with:
Manuel Clergue France
Anita Pasotti Italy
Yuto Nakashima Japan
Markus L. Schmid Germany
Victor Mitrana Spain
Boting Yang Canada
Will Smart New Zealand
Stephen Dignum United Kingdom
Jean-Philippe Bossuat Switzerland
Michael Dom Germany
Philippe Collard relative to Manuel Clergue France Manuel Clergue's profile →
Citations per field
00.5×1.5×
Manuel Clergue · 1×
Citations per year

Countries citing papers authored by Philippe Collard

Since Specialization
Citations

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

Fields of papers citing papers by Philippe Collard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 7 scholars most cited alongside Philippe Collard, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Philippe Collard Line = papers co-authored together Philippe Collard links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 200572
2
Fitness Distance Correlation And Problem Difficulty For Genetic Programming
200215
3 200215
4 199713
5 200211
6
Fitness Distance Correlation, as statistical measure of Genetic Algorithm difficulty, revisited.
19988
7 20117
8 20116
9 20025
10 20034
11 20031

About Philippe Collard

Philippe Collard is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Molecular Biology, Genetics and Biomedical Engineering, having authored 11 papers that have together received 157 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (11 papers), Evolutionary Algorithms and Applications (10 papers), Advanced Multi-Objective Optimization Algorithms (4 papers), Evolution and Genetic Dynamics (2 papers), Artificial Immune Systems Applications (1 paper), CRISPR and Genetic Engineering (1 paper), Cellular Automata and Applications (1 paper) and Fuzzy Logic and Control Systems (1 paper). The work is most often cited by research in Artificial Intelligence (131 citations), Computational Theory and Mathematics (63 citations), Genetics (24 citations), Industrial and Manufacturing Engineering (4 citations) and Molecular Biology (23 citations). Philippe Collard has collaborated with scholars based in France, Switzerland and Italy. Frequent co-authors include Manuel Clergue, Leonardo Vanneschi, Marco Tomassini, Sebástien Vérel, David Simoncini, Giancarlo Mauri and Yuri Pirola. Their work appears in journals such as Theoretical Computer Science, Evolutionary Computation, International Journal of Artificial Intelligence Tools, IRIS and arXiv (Cornell University).

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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