no code implementations • 14 Jun 2023 • Felix Lanfermann, Qiqi Liu, Yaochu Jin, Sebastian Schmitt
In this study we focus on utilizing the concept identification technique for finding relevant and viable energy management configurations from a very large data set of Pareto-optimal solutions.
no code implementations • 13 Jan 2023 • Felix Lanfermann, Sebastian Schmitt, Patricia Wollstadt
To support the novel understanding of concept identification, we consider a simulated data set from a decision-making problem in the energy management domain and show that the identified clusters are more interpretable with respect to relevant feature subsets than clusters found by common clustering algorithms and are thus more suitable to support a decision maker.
no code implementations • 9 Jun 2022 • Felix Lanfermann, Sebastian Schmitt
In this work, an approach to define meaningful and consistent concepts in an existing engineering dataset is presented.