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SINDyc And MCMC Framework
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freba
SINDyc And MCMC Framework
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e56ca82e
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Jun 28, 2020
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freba
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* Description
Code utilized to generate the results in the publication "Prosumer Response Estimation using SINDyc in conjunction with Markov-chain Monte-Carlo Sampling" (see Section [[Reference paper]]).
* TODO Prerequisites
- numpy
- pandas
- collections
- control
- pySINDy :: https://github.com/luckystarufo/pySINDy/
- Recent package version, untested :: https://github.com/dynamicslab/
- python :: Tested with version =3.7.7=.
- numpy :: https://pypi.org/project/numpy/. Tested with version =1.18.5=.
- pandas :: https://pypi.org/project/pandas/. Tested with version =1.0.5=.
- control :: https://pypi.org/project/control/. Tested with version =0.8.2=.
- pystan :: https://pypi.org/project/pystan/. Tested with version =2.19.1.1=.
- pySINDy :: https://github.com/luckystarufo/pySINDy/.
- Recent package version, untested :: https://github.com/dynamicslab/.
* TODO Installation
* TODO License
This code is licensed under the MIT license. See the =License= statement in this directory.
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Banis, F.; Madsen, H.; Poulsen, N.K.; Guericke, D. Prosumer Response Estimation Using SINDyc in Conjunction with Markov-Chain Monte-Carlo Sampling. Energies 2020, 13, 3183.
#+END_QUOTE
* Miscellaneous
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* Footnotes
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