Evolutionary Algorithms for Segment Optimization in Vectorial GP-Reference-Cited by-同舟云学术

Evolutionary Algorithms for Segment Optimization in Vectorial GP

Published:2023-07-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Companion Conference on Genetic and Evolutionary Computation
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Author:

Fleck Philipp¹^ORCID,Winkler Stephan¹^ORCID,Kommenda Michael¹^ORCID,Silva Sara²^ORCID,Vanneschi Leonardo³^ORCID,Affenzeller Michael¹^ORCID

Affiliation:

1. Heuristic and Evolutionary Algorithms Laboratory, University of Applied Sciences Upper Austria, Hagenberg im Mühlkreis, Austria

2. LASIGE, Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal

3. NOVA Information Management School, Universidade Nova de Lisboa, Lisbon, Portugal

Funder

FFG

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3583133.3590668

Reference16 articles.

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3. Time Series FeatuRe Extraction on basis of Scalable Hypothesis tests (tsfresh – A Python package)

4. Russell Eberhart and James Kennedy . 1995 . Particle swarm optimization . In Proceedings of the IEEE international conference on neural networks , Vol. 4 . Citeseer , 1942--1948. Russell Eberhart and James Kennedy. 1995. Particle swarm optimization. In Proceedings of the IEEE international conference on neural networks, Vol. 4. Citeseer, 1942--1948.

5. Philipp Fleck Stephan Winkler Michael Kommenda and Michael Affenzeller. 2021. Garmmar-based Vectorial Genetig Programming for Symbolic Regression. In Genetic Programming Theory and Practice XVIII Wolfgang Banzhaf Leonardo Trujillo Stephan Winkler and Bill Worzel (Eds.). Springer Nature Singapore Pte Ltd. Philipp Fleck Stephan Winkler Michael Kommenda and Michael Affenzeller. 2021. Garmmar-based Vectorial Genetig Programming for Symbolic Regression. In Genetic Programming Theory and Practice XVIII Wolfgang Banzhaf Leonardo Trujillo Stephan Winkler and Bill Worzel (Eds.). Springer Nature Singapore Pte Ltd.