Category Archives: Uncategorized

EvoStar2021 conference goes online

EvoStar2021 conference goes online and will be held from the 7th to the 9th of April of 2021.
Our paper “Bayesian Networks for Mood Prediction Using Unobstrusive Ecological Momentary Assesments” (Margarita Alejandra Rebolledo Coy, A.E. Eiben and Thomas Bartz-Beielstein), see program overview, that holds the links to all the sessions and for the Full Programme and details. The opening session and the keynotes will be live-streamed in the SPECIES YouTube Channel:

Check the website for additional information:

Version 1.7 of imputeTS R package released

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Version 1.7 of the R package „imputeTS: Time Series Missing Value Imputation“ has been recently released on CRAN.
The package, which is developed within the SPOTSeven research group, provides several functions that help with missing data in time series. This includes simple and fast imputation algorithms, several advanced imputation algorithms and missing data visualization functions.
The imputeTS package can be found on CRAN. For installation execute install.packages(“imputeTS”) in R. A short introduction into usage can be found in the README.
User visible changes in version 1.7:

  • Improved compatibility for input of advanced time series objects like zoo and xts
  • Enabled multivariate input (data.frame, mts, matrix,…)
  • Improved x-labels for na.distributionBar plot
  • Revised user manual
  • Revised usage examples
  • Better worded error messages

For a complete list of all changes take a look into the package NEWS on CRAN.

Multi-fidelity modeling and optimization of biogas plants – free article available for 50 days!

Anyone who clicks on the link until August 24, 2016, will be taken to the final version of the article “Multi-fidelity modeling and optimization of biogas plants” (Martin Zaefferer, Daniel Gaida, Thomas Bartz-Beielstein) on ScienceDirect for free. No sign up or registration is needed – just click and read! Here is the link:

Highlights of this article read as follows:

  • Accurate and fast simulation models mandatory for the optimization of biogas plants.
  • Improve precision of simulation models without increasing the number of evaluations.
  • Combining results: complex simulator, simple estimation-based model and surrogate model.
  • Advantages and limitations of multi-fidelity modeling approaches are discussed.