Follow
Michael Kommenda
Title
Cited by
Cited by
Year
Architecture and design of the heuristiclab optimization environment
S Wagner, G Kronberger, A Beham, M Kommenda, A Scheibenpflug, ...
Advanced Methods and Applications in Computational Intelligence, 197-261, 2014
1352014
Effects of constant optimization by nonlinear least squares minimization in symbolic regression
M Kommenda, G Kronberger, S Winkler, M Affenzeller, S Wagner
Proceedings of the 15th annual conference companion on Genetic andá…, 2013
652013
Contemporary Symbolic Regression Methods and their Relative Performance
W La Cava, P Orzechowski, B Burlacu, FO de Franša, M Virgolin, Y Jin, ...
arXiv preprint arXiv:2107.14351, 2021
562021
Using FE calculations and data-based system identification techniques to model the nonlinear behavior of PMSMs
G Bramerdorfer, SM Winkler, M Kommenda, G Weidenholzer, S Silber, ...
IEEE Transactions on Industrial Electronics 61 (11), 6454-6462, 2014
512014
Parameter identification for symbolic regression using nonlinear least squares
M Kommenda, B Burlacu, G Kronberger, M Affenzeller
Genetic Programming and Evolvable Machines 21 (3), 471-501, 2020
492020
Advanced Methods and Applications in Computational Intelligence, volume 6 of Topics in Intelligent Engineering and Informatics, chapter Architecture and Design of theá…
S Wagner, G Kronberger, A Beham, M Kommenda, A Scheibenpflug, ...
Springer 53 (55), 197-261, 2014
412014
Macro-economic time series modeling and interaction networks
G Kronberger, S Fink, M Kommenda, M Affenzeller
European Conference on the Applications of Evolutionary Computation, 101-110, 2011
382011
Gaining deeper insights in symbolic regression
M Affenzeller, SM Winkler, G Kronberger, M Kommenda, B Burlacu, ...
Genetic Programming Theory and Practice XI, 175-190, 2014
372014
Operon C++ an efficient genetic programming framework for symbolic regression
B Burlacu, G Kronberger, M Kommenda
Proceedings of the 2020 Genetic and Evolutionary Computation Conferenceá…, 2020
312020
Evolving simple symbolic regression models by multi-objective genetic programming
M Kommenda, G Kronberger, M Affenzeller, SM Winkler, B Burlacu
Genetic Programming Theory and Practice XIII, 1-19, 2016
252016
HeuristicLab 3.3: A unified approach to metaheuristic optimization
S Wagner, A Beham, G Kronberger, M Kommenda, E Pitzer, M Kofler, ...
Actas del sÚptimo congreso espa˝ol sobre MetaheurÝsticas, Algoritmosá…, 2010
252010
Visualization of genetic lineages and inheritance information in genetic programming
B Burlacu, M Affenzeller, M Kommenda, S Winkler, G Kronberger
Proceedings of the 15th annual conference companion on Genetic andá…, 2013
232013
On the architecture and implementation of tree-based genetic programming in HeuristicLab
M Kommenda, G Kronberger, S Wagner, S Winkler, M Affenzeller
Proceedings of the 14th annual conference companion on Genetic andá…, 2012
232012
Evolution of covariance functions for gaussian process regression using genetic programming
G Kronberger, M Kommenda
International Conference on Computer Aided Systems Theory, 308-315, 2013
212013
Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of Two-Dimensional Flows in Single-Screw Extrusion
W Roland, M Kommenda, C Marschik, J Miethlinger
Polymers 11 (2), 334, 2019
182019
Shape-Constrained Symbolic Regression—Improving Extrapolation with Prior Knowledge
G Kronberger, FO de Franša, B Burlacu, C Haider, M Kommenda
Evolutionary computation 30 (1), 75-98, 2022
172022
Simulation-Based Optimization with HeuristicLab: Practical Guidelines and Real-World Applications
M Affenzeller, A Beham, S Vonolfen, E Pitzer, SM Winkler, S Hutterer, ...
Applied Simulation and Optimization, 3-38, 2015
162015
Symbolic regression by exhaustive search: reducing the search space using syntactical constraints and efficient semantic structure deduplication
L Kammerer, G Kronberger, B Burlacu, SM Winkler, M Kommenda, ...
Genetic Programming Theory and Practice XVII, 79-99, 2020
142020
Prediction of stress-strain curves for aluminium alloys using symbolic regression
E Kabliman, AH Kolody, M Kommenda, G Kronberger
AIP Conference Proceedings 2113 (1), 180009, 2019
142019
Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems
G Kronberger, M Kommenda, E Lughofer, S Saminger-Platz, ...
Applied Soft Computing 69, 610-624, 2018
132018
The system can't perform the operation now. Try again later.
Articles 1–20