Commit 271ba279 authored by Janis Jatnieks's avatar Janis Jatnieks
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Update README.md, spelling and abstract.

parent 672838f3
# Intro # Intro
Surrogate playground is an [automated machine learning approach](https://en.wikipedia.org/wiki/Automated_machine_learning) written for rapidly Surrogate playground is an [automated machine learning approach](https://en.wikipedia.org/wiki/Automated_machine_learning) written
screening a large number of different ML models to serve as [surrogates](https://en.wikipedia.org/wiki/Surrogate_model) for a slow runnig simulator. for rapidly screening a large number of different machine learning models to serve as [surrogates](https://en.wikipedia.org/wiki/Surrogate_model)
for reaplcing a slow running simulator. This code was written for a reactive transport application where a fluid flow model (hydrodynamics) is
This was written for a reactive transport application where coupled to a geochemistry simulator (reactions in time and space) to simulate scenarios such as underground storage of CO2 or
a fluid flow model (hydrodynamics) is coupled to a hydrogen storage for excess energy from wind farms. The challenge for such applications is that the geochemistry simulator is
geochemistry simulator (reactions in time and space) typically slow compared to fluid dynamics and constitutes the main bottleneck for producing highly detailed simulations of
to simulate scenarios such as underground storage of CO2 or such application scenarios. This auto-ML approach attempts to find machine learning models that can replace the slow running simulator when trained on input-output data from the geochemistry simulator. The code may be of more general interest as this prototype can be used to screen many different machine learning models for any regression problem in general. It also contains a demonstration example using the Boston housing standard data-set.
hydrogen storage for excess energy from wind farms. The challange for such appliactions is that
geochemistry simulators are quite slow copared to fluid
dynamics and constitute the main bottleneck for producing
highly detaled simulations of such application scenarios.
# Materials # Materials
For the proof-of-concept research pioneering the use of surrogate models for reactive transport geochemistry, see our [paper here](https://www.sciencedirect.com/science/article/pii/S1876610216310050) and our [EGU Poster presentation summarizing this work here](https://presentations.copernicus.org/EGU2016-12923_presentation.pdf). For the proof-of-concept research pioneering the use of surrogate models for reactive transport geochemistry, see our [paper here](https://www.sciencedirect.com/science/article/pii/S1876610216310050) and our [EGU Poster presentation summarizing this work here](https://presentations.copernicus.org/EGU2016-12923_presentation.pdf).
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