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Thermodynamics-informed Symbolic Regression - A Tool for the Thermodynamic Equation of State Development - v2.0.0-beta

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 04 Feb 2025Publisher:ZenodoFunded by:DFG | unidentified
Authors: Martinek, Viktor; Frotscher, Ophelia; Richter, Markus; Herzog, Roland;
Code repository: https://github.com/scoop-group/TiSR/tree/v0.1.1-beta

doi: 10.5281/zenodo.15100641 , 10.5281/zenodo.14800621 , 10.5281/zenodo.14800761 , 10.5281/zenodo.8317546

Thermodynamics-informed Symbolic Regression - A Tool for the Thermodynamic Equation of State Development - v2.0.0-beta

Abstract

This code base is based on the work of the project "Machine Learning and Optimal Experimental Design for Thermodynamic Property Modeling" in the DFG priority program SPP2331. It implements an adapted NSGA-II genetic algorithm for symbolic regression and is aimed at the development of thermodynamic equations of state. The project and the code are a work-in-progress and there are many more features planned. For more details on past and future uses, a paper accompanying this code is available at arxiv.This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) within the Priority Programme SPP 2331: "Machine Learning in Chemical Engineering" - project no. 466528284 - HE 6077/14-1 and RI 2482/10-1

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average