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Identification of Energy Management Configuration Concepts from a Set of Pareto-optimal Solutions
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.
Understanding Concept Identification as Consistent Data Clustering Across Multiple Feature Spaces
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.
Concept Identification for Complex Engineering Datasets
In this work, an approach to define meaningful and consistent concepts in an existing engineering dataset is presented.
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