Lars Gräning

14 papers B 3C 3Journal 3Unranked 3
YearRankTypeTitle / Venue / Authors
2024 J jnl
Robustness investigation of quality measures for the assessment of machine learning models.
CoRR
Thomas Most, Lars Gräning, Sebastian Wolff
2016 — conf
Automatic energy management controller design for hybrid electric vehicles.
SSCI
Tobias Rodemann, Lars Gräning, Ken Nishikawa
2014 J jnl
Shape mining: A holistic data mining approach for engineering design.
Adv. Eng. Informatics
Lars Gräning, Bernhard Sendhoff
2014 — —
Shape mining: knowledge extraction from engineering design data.
Lars Gräning
2013 C conf
Quantifying Flow Field Distances Based on a Compact Streamline Representation.
IDEAL
Lars Gräning, Thomas Ramsay
2012 — conf
Application of Sensitivity Analysis for an Improved Representation in Evolutionary Design Optimization.
ICGEC
Lars Gräning, Stefan Menzel, Thomas Ramsay, Bernhard Sendhoff
2010 — conf
Towards Directed Open-Ended Search by a Novelty Guided Evolution Strategy.
PPSN (2)
Lars Gräning, Nikola Aulig, Markus Olhofer
2009 C conf
Interaction Detection in Aerodynamic Design Data.
IDEAL
Lars Gräning, Markus Olhofer, Bernhard Sendhoff
2008 J jnl
Knowledge Extraction from Aerodynamic Design Data and its Application to 3D Turbine Blade Geometries.
J. Math. Model. Algorithms
Lars Gräning, Stefan Menzel, Martina Hasenjäger, Thomas Bihrer, Markus Olhofer, Bernhard Sendhoff
2008 B conf
Unsupervised extraction of design components for a 3D parts-based representation.
IJCNN
Zdravko Bozakov, Lars Gräning, Stephan Hasler, Heiko Wersing, Stefan Menzel
2007 — ch.
Individual-based Management of Meta-models for Evolutionary Optimization with Application to Three-Dimensional Blade Optimization.
Evolutionary Computation in Dynamic and Uncertain Environments
Lars Gräning, Yaochu Jin, Bernhard Sendhoff
2007 C conf
Knowledge Extraction from Unstructured Surface Meshes.
IDEAL
Lars Gräning, Markus Olhofer, Bernhard Sendhoff
2006 B conf
Generalization Improvement in Multi-Objective Learning.
IJCNN
Lars Gräning, Yaochu Jin, Bernhard Sendhoff
2005 B conf
Efficient evolutionary optimization using individual-based evolution control and neural networks: A comparative study.
ESANN
Lars Gräning, Yaochu Jin, Bernhard Sendhoff