Complexity Analysis of GPA and GPA-ES Algorithms for Symbolic Regression
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F24%3A39921850" target="_blank" >RIV/00216275:25530/24:39921850 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/book/10.1007/978-3-031-94770-4" target="_blank" >https://link.springer.com/book/10.1007/978-3-031-94770-4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-94770-4_5" target="_blank" >10.1007/978-3-031-94770-4_5</a>
Alternative languages
Result language
angličtina
Original language name
Complexity Analysis of GPA and GPA-ES Algorithms for Symbolic Regression
Original language description
This paper presents a complexity analysis of Genetic Programming (GP) for Symbolic Regression. Two algorithms, classic GPA and the hybrid method GPA + ES, are introduced and then compared. First, the implementations and properties of these methods are described. Results indicate that both algorithms have exponential time and space complexity, with GPA + ES not being asymptotically less demanding than GPA. However, polynomial complexity is achievable when certain parameters are set as constants. This analysis offers insights into algorithm performance and applicability, particularly for analyzing large datasets.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20200 - Electrical engineering, Electronic engineering, Information engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Artificial Intelligence and System Engineering: Proceedings of 8th Computational Methods in Systems and Software 2024, Volume 2 (Lecture Notes in Networks and Systems. Vol. 1490)
ISBN
978-3-031-96758-0
ISSN
2367-3370
e-ISSN
2367-3389
Number of pages
9
Pages from-to
"40 "- 48
Publisher name
Springer Science and Business Media
Place of publication
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Event location
online
Event date
Oct 25, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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