| Contemporary Symbolic Regression Methods and their Relative Performance W La Cava, P Orzechowski, B Burlacu, FO de França, M Virgolin, Y Jin, ... arXiv preprint arXiv:2107.14351, 2021 | 303 | 2021 |
| 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 | 196 | 2014 |
| 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 | 130 | 2020 |
| Operon C++ an efficient genetic programming framework for symbolic regression B Burlacu, G Kronberger, M Kommenda Proceedings of the 2020 Genetic and Evolutionary Computation Conference …, 2020 | 127 | 2020 |
| 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 and …, 2013 | 79 | 2013 |
| 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 | 60 | 2014 |
| Shape-Constrained Symbolic Regression—Improving Extrapolation with Prior Knowledge G Kronberger, FO de França, B Burlacu, C Haider, M Kommenda Evolutionary computation 30 (1), 75-98, 2022 | 58 | 2022 |
| Advanced methods and applications in computational intelligence S Wagner, G Kronberger, A Beham, M Kommenda, A Scheibenpflug, ... Topics in Intelligent Engineering and Informatics 6, 197-261, 2014 | 52 | 2014 |
| 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 | 47 | 2014 |
| 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 | 41 | 2016 |
| Macro-economic time series modeling and interaction networks G Kronberger, S Fink, M Kommenda, M Affenzeller Applications of Evolutionary Computation: EvoApplications 2011: EvoCOMNET …, 2011 | 40 | 2011 |
| Application of Symbolic Regression for Constitutive Modeling of Plastic Deformation E Kabliman, AH Kolody, J Kronsteiner, M Kommenda, G Kronberger Applications in Engineering Science, 100052, 2021 | 38 | 2021 |
| 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 | 32 | 2020 |
| 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 | 29 | 2019 |
| 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 and …, 2013 | 29 | 2013 |
| HeuristicLab 3.3: A unified approach to metaheuristic optimization S Wagner, A Beham, G Kronberger, M Kommenda, E Pitzer, M Kofler, ... Actas del séptimo congreso español sobre Metaheurísticas, Algoritmos …, 2010 | 29 | 2010 |
| 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 and …, 2012 | 28 | 2012 |
| Complexity measures for multi-objective symbolic regression M Kommenda, A Beham, M Affenzeller, G Kronberger Computer Aided Systems Theory–EUROCAST 2015: 15th International Conference …, 2015 | 26 | 2015 |
| Evolution of covariance functions for gaussian process regression using genetic programming G Kronberger, M Kommenda Computer Aided Systems Theory-EUROCAST 2013: 14th International Conference …, 2013 | 26 | 2013 |
| Prediction of stress-strain curves for aluminium alloys using symbolic regression E Kabliman, AH Kolody, M Kommenda, G Kronberger AIP Conference Proceedings 2113 (1), 2019 | 25 | 2019 |
Gabriel KronbergerUniversity of Applied Sciences Upper Austria確認したメール アドレス: fh-hagenberg.at