Thomas Runkler
Thomas Runkler
Professor of Computer Science, Siemens AG, Technische Universität München
Geverifieerd e-mailadres voor siemens.com
Geciteerd door
Geciteerd door
Fuzzy cluster analysis: methods for classification, data analysis and image recognition
F Höppner, F Klawonn, R Kruse, T Runkler
John Wiley & Sons, 1999
Selection of appropriate defuzzification methods using application specific properties
TA Runkler
IEEE transactions on fuzzy systems 5 (1), 72-79, 1997
Data Analytics
TA Runkler
Wiesbaden: Springer. doi 10, 978-3, 2012
Alternating cluster estimation: A new tool for clustering and function approximation
TA Runkler, JC Bezdek
IEEE transactions on fuzzy systems 7 (4), 377-393, 1999
A set of axioms for defuzzification strategies towards a theory of rational defuzzification operators
TA Runkler, M Glesner
[Proceedings 1993] Second IEEE International Conference on Fuzzy Systems …, 1993
Web mining with relational clustering
TA Runkler, JC Bezdek
International Journal of Approximate Reasoning 32 (2-3), 217-236, 2003
Fuzzy clustering by particle swarm optimization
TA Runkler, C Katz
2006 IEEE international conference on fuzzy systems, 601-608, 2006
Distributed supply chain management using ant colony optimization
CA Silva, JMC Sousa, TA Runkler, JMGS Da Costa
European Journal of Operational Research 199 (2), 349-358, 2009
Ant colony optimization of clustering models
TA Runkler
International Journal of Intelligent Systems 20 (12), 1233-1251, 2005
Two cooperative ant colonies for feature selection using fuzzy models
SM Vieira, JMC Sousa, TA Runkler
Expert Systems with Applications 37 (4), 2714-2723, 2010
Interpretable policies for reinforcement learning by genetic programming
D Hein, S Udluft, TA Runkler
Engineering Applications of Artificial Intelligence 76, 158-169, 2018
Neural relation extraction within and across sentence boundaries
P Gupta, S Rajaram, H Schütze, T Runkler
Proceedings of the AAAI conference on artificial intelligence 33 (01), 6513-6520, 2019
Rescheduling and optimization of logistic processes using GA and ACO
CA Silva, JMC Sousa, TA Runkler
Engineering Applications of Artificial Intelligence 21 (3), 343-352, 2008
Using a local discovery ant algorithm for Bayesian network structure learning
PC Pinto, A Nagele, M Dejori, TA Runkler, JMC Sousa
IEEE transactions on evolutionary computation 13 (4), 767-779, 2009
Tinyol: Tinyml with online-learning on microcontrollers
H Ren, D Anicic, TA Runkler
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
Wasp swarm algorithm for dynamic MAX-SAT problems
PC Pinto, TA Runkler, JMC Sousa
International conference on adaptive and natural computing algorithms, 350-357, 2007
Particle swarm optimization for generating interpretable fuzzy reinforcement learning policies
D Hein, A Hentschel, T Runkler, S Udluft
Engineering Applications of Artificial Intelligence 65, 87-98, 2017
Classification and prediction of road traffic using application-specific fuzzy clustering
C Stutz, TA Runkler
IEEE Transactions on Fuzzy Systems 10 (3), 297-308, 2002
Extended defuzzification methods and their properties
TA Runkler
Proceedings of IEEE 5th international fuzzy systems 1, 694-700, 1996
Current and future development in neural computation in steel processing
M Schlang, B Lang, T Poppe, T Runkler, K Weinzierl
Control engineering practice 9 (9), 975-986, 2001
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