| Genetic algorithm essentials O Kramer Springer, 2017 | 269 | 2017 |
| Long-term research challenges in wind energy–a research agenda by the European Academy of Wind Energy GAM Van Kuik, J Peinke, R Nijssen, D Lekou, J Mann, JN Sørensen, ... Wind energy science 1 (1), 1-39, 2016 | 154 | 2016 |
| A review of constraint-handling techniques for evolution strategies O Kramer Applied Computational Intelligence and Soft Computing 2010, 2010 | 140 | 2010 |
| Dimensionality reduction with unsupervised nearest neighbors O Kramer Springer, 2013 | 129* | 2013 |
| Machine learning ensembles for wind power prediction J Heinermann, O Kramer Renewable Energy 89, 671-679, 2016 | 105 | 2016 |
| Evolutionary self-adaptation: a survey of operators and strategy parameters O Kramer Evolutionary Intelligence 3 (2), 51-65, 2010 | 99 | 2010 |
| Comparing support vector regression for PV power forecasting to a physical modeling approach using measurement, numerical weather prediction, and cloud motion data B Wolff, J Kühnert, E Lorenz, O Kramer, D Heinemann Solar Energy 135, 197-208, 2016 | 94 | 2016 |
| Energy informatics C Goebel, HA Jacobsen, V del Razo, C Doblander, J Rivera, J Ilg, C Flath, ... Business & Information Systems Engineering 6 (1), 25-31, 2014 | 90 | 2014 |
| Self-adaptive heuristics for evolutionary computation O Kramer Springer, 2008 | 83 | 2008 |
| Evolution of human-competitive agents in modern computer games S Priesterjahn, O Kramer, A Weimer, A Goebels 2006 IEEE International Conference on Evolutionary Computation, 777-784, 2006 | 66 | 2006 |
| Derivative-free optimization O Kramer, DE Ciaurri, S Koziel Computational optimization, methods and algorithms, 61-83, 2011 | 64 | 2011 |
| Computational intelligence: eine Einführung O Kramer Springer-Verlag, 2009 | 59 | 2009 |
| Short-term wind energy forecasting using support vector regression O Kramer, F Gieseke Soft Computing Models in Industrial and Environmental Applications, 6th …, 2011 | 52 | 2011 |
| Iterated local search with Powell’s method: a memetic algorithm for continuous global optimization O Kramer Memetic Computing 2 (1), 69-83, 2010 | 49 | 2010 |
| Statistical learning for short-term photovoltaic power predictions B Wolff, E Lorenz, O Kramer Computational sustainability, 31-45, 2016 | 48 | 2016 |
| Optimization of elastic properties and weaving patterns of woven composites IAA Bakar, O Kramer, S Bordas, T Rabczuk Composite Structures 100, 575-591, 2013 | 45 | 2013 |
| On three new approaches to handle constraints within evolution strategies O Kramer, HP Schwefel Natural Computing 5 (4), 363-385, 2006 | 43 | 2006 |
| Learning the track and planning ahead in a car racing controller J Quadflieg, M Preuss, O Kramer, G Rudolph Proceedings of the 2010 IEEE Conference on Computational Intelligence and …, 2010 | 42 | 2010 |
| Fast and simple gradient-based optimization for semi-supervised support vector machines F Gieseke, A Airola, T Pahikkala, O Kramer Neurocomputing 123, 23-32, 2014 | 41 | 2014 |
| Dimensionality reduction by unsupervised k-nearest neighbor regression O Kramer 2011 10th International Conference on Machine Learning and Applications and …, 2011 | 38 | 2011 |
