Newer
Older
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]]).
- 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/.
This code is licensed under the MIT license. See the =License= statement in this directory.
* Reference paper
#+BEGIN_QUOTE
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