Artificial Intelligence in Physical Sciences: Symbolic Regression Trends and Perspectives
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Abstract
Symbolic regression (SR) is a machine learning-based regression method based on genetic programming principles that integrates techniques and processes from heterogeneous scientific fields and is capable of providing analytical equations purely from data. This remarkable characteristic diminishes the need to incorporate prior knowledge about the investigated system. SR can spot profound and elucidate ambiguous relations that can be generalizable, applicable, explainable and span over most scientific, technological, economical, and social principles. In this review, current state of the art is documented, technical and physical characteristics of SR are presented, the available programming techniques are…
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206
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- FWCI
- 34.11
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- 100%
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Authors
3Topics & keywords
Topics
Keywords
- Symbolic regression
- Genetic programming
- Computer science
- Regression
- Artificial intelligence
- Regression analysis
- Data science
- Machine learning
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