Population Dynamics in Genetic Programming for Dynamic Symbolic Regression

This paper investigates the application of genetic programming (GP) for dynamic symbolic regression (SR), addressing the challenge of adapting machine learning models to evolving data in practical applications. Benchmark instances with changing underlying functions over time are defined to assess th...

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Bibliographic Details
Published in:	Applied sciences Vol. 14; no. 2; p. 596
Main Authors:	Fleck, Philipp, Werth, Bernhard, Affenzeller, Michael
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.01.2024
Subjects:	Adaptation Algorithms Artificial intelligence dynamic optimization Genetic algorithms genetic programming Genetic research Interoperability Machine learning Neural networks Optimization Population biology Programming languages symbolic regression Austria Germany
ISSN:	2076-3417, 2076-3417
Online Access:	Get full text
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