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Lars Graening
Lars Graening
Dynardo GmbH, an Ansys company
Verified email at ansys.com - Homepage
Title
Cited by
Cited by
Year
Generalization improvement in multi-objective learning
L Graning, Y Jin, B Sendhoff
The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006
462006
Efficient evolutionary optimization using individual-based evolution control and neural networks: A comparative study.
L Gräning, Y Jin, B Sendhoff
ESANN, 273-278, 2005
392005
Shape mining: A holistic data mining approach for engineering design
L Graening, B Sendhoff
Advanced Engineering Informatics 28 (2), 166-185, 2014
382014
Individual-based management of meta-models for evolutionary optimization with application to three-dimensional blade optimization
L Gräning, Y Jin, B Sendhoff
Evolutionary computation in dynamic and uncertain environments, 225-250, 2007
352007
Knowledge extraction from aerodynamic design data and its application to 3d turbine blade geometries
L Graening, S Menzel, M Hasenjäger, T Bihrer, M Olhofer, B Sendhoff
Journal of Mathematical Modelling and Algorithms 7, 329-350, 2008
332008
Towards directed open-ended search by a novelty guided evolution strategy
L Graening, N Aulig, M Olhofer
Parallel Problem Solving from Nature, PPSN XI: 11th International Conference …, 2010
142010
Analysis of crush-damaged carbon-fiber-reinforced-polymer (CFRP) composites with optimization-assisted post-peak-stress modeling
S Dong, L Gräning, K Carney, A Sheldon
Journal of Composite Materials 55 (6), 759-774, 2021
72021
Model-guided evolution strategies for dynamically balancing exploration and exploitation
E Reehuis, J Kruisselbrink, M Olhofer, L Graening, B Sendhoff, T Bäck
The Biannual International Conference on Artificial Evolution. Universite d …, 2011
62011
Unsupervised extraction of design components for a 3D parts-based representation
Z Bozakov, L Graening, S Hasler, H Wersing, S Menzel
2008 IEEE International Joint Conference on Neural Networks (IEEE World …, 2008
62008
Application of Sensitivity Analysis for an Improved Representation in Evolutionary Design Optimization
L Graening, S Menzel, T Ramsay, B Sendhoff
Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International …, 2012
52012
Modeling design and flow feature interactions for automotive synthesis
M Rath, L Graening
Intelligent Data Engineering and Automated Learning-IDEAL 2011: 12th …, 2011
52011
Flow field data mining based on a compact streamline representation
L Graening, T Ramsay
SAE Technical Paper, 2015
42015
Interaction detection in aerodynamic design data
L Graening, M Olhofer, B Sendhoff
Intelligent Data Engineering and Automated Learning-IDEAL 2009: 10th …, 2009
42009
Aerodynamic design optimization using information extracted from analysis of unstructured surface meshes
L Graning, M Olhofer, B Sendhoff
US Patent 9,659,122, 2017
32017
Parametric Optimization of CAE Material Models for Carbon-Fiber-Reinforced Polymer (CFRP) Composites
S Dong, L Gräning, K Carney, A Sheldon
NAFEMS World Congress, 2017
22017
Automatic energy management controller design for hybrid electric vehicles
T Rodemann, L Gräning, K Nishikawa
2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2016
22016
Knowledge Incorporation into Evolutionary Algorithms to speed up Aerodynamic Design Optimizations
S Ramanathan, L Graening
Universitat Stuttgart, 2009
22009
Knowledge extraction from unstructured surface meshes
L Graening, M Olhofer, B Sendhoff
International Conference on Intelligent Data Engineering and Automated …, 2007
22007
Designing real-world objects using the interaction between multiple design variables and system properties
L Gräning
US Patent App. 12/891,992, 2011
12011
Quantifying Vector Field Distances Based on a Reduced Stream Line Representations
L Gräning, T Ramsay
Int. Conf. on Intelligent Data Engeneering and Automated Learning (IDEAL …, 0
1
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