Martin Holena
Martin Holena
Unknown affiliation
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Cited by
Cited by
Statistical analysis of past catalytic data on oxidative methane coupling for new insights into the composition of high-performance catalysts
U Zavyalova, M Holena, R Schlögl, M Baerns
ChemCatChem 3 (12), 1935-1947, 2011
Application of a genetic algorithm and a neural network for the discovery and optimization of new solid catalytic materials
U Rodemerck, M Baerns, M Holena, D Wolf
Applied Surface Science 223 (1-3), 168-174, 2004
Catalyst Development for CO2 Hydrogenation to Fuels
U Rodemerck, M Holeňa, E Wagner, Q Smejkal, A Barkschat, M Baerns
ChemCatChem 5 (7), 1948-1955, 2013
Feedforward neural networks in catalysis: A tool for the approximation of the dependency of yield on catalyst composition, and for knowledge extraction
M Holeňa, M Baerns
Catalysis Today 81 (3), 485-494, 2003
Comparing middleware concepts for advanced healthcare system architectures
B Blobel, M Holena
International journal of medical informatics 46 (2), 69-85, 1997
The GUHA method and its meaning for data mining
P Hájek, M Holeňa, J Rauch
Journal of Computer and System Sciences 76 (1), 34-48, 2010
Developing catalytic materials for the oxidative coupling of methane through statistical analysis of literature data
EV Kondratenko, M Schlüter, M Baerns, D Linke, M Holena
Catalysis Science & Technology 5 (3), 1668-1677, 2015
New catalytic materials for the high-temperature synthesis of hydrocyanic acid from methane and ammonia by high-throughput approach
S Moehmel, N Steinfeldt, S Engelschalt, M Holena, S Kolf, M Baerns, ...
Applied Catalysis A: General 334 (1-2), 73-83, 2008
Fuzzy hypotheses testing in the framework of fuzzy logic
M Holeňa
Fuzzy Sets and Systems 145 (2), 229-252, 2004
Combinatorial development of solid catalytic materials: design of high-throughput experiments, data analysis, data mining
M Baerns, M Holena
World Scientific, 2009
The influence of preparation variables on the performance of Pd/Al2O3 catalyst in the hydrogenation of 1, 3-butadiene: Building a basis for reproducible catalyst synthesis
T Cukic, R Kraehnert, M Holena, D Herein, D Linke, U Dingerdissen
Applied Catalysis A: General 323, 25-37, 2007
An approach to structure determination and estimation of hierarchical Archimedean copulas and its application to Bayesian classification
J Górecki, M Hofert, M Holeňa
Journal of Intelligent Information Systems 46 (1), 21-59, 2016
Benchmarking Gaussian processes and random forests surrogate models on the BBOB noiseless testbed
L Bajer, Z Pitra, M Holeňa
Proceedings of the Companion Publication of the 2015 Annual Conference on …, 2015
Fuzzy hypotheses for GUHA implications
M Holeňa
Fuzzy Sets and Systems 98 (1), 101-125, 1998
Optimization of catalysts using specific, description-based genetic algorithms
M Holena, T Cukic, U Rodemerck, D Linke
Journal of chemical information and modeling 48 (2), 274-282, 2008
Formal logics of discovery and hypothesis formation by machine
P Hájek, M Holeňa
Theoretical Computer Science 292 (2), 345-357, 2003
Surrogate model for continuous and discrete genetic optimization based on RBF networks
L Bajer, M Holeňa
International Conference on Intelligent Data Engineering and Automated …, 2010
CORBA security services for health information systems
B Blobel, M Holena
International journal of medical informatics 52 (1-3), 29-37, 1998
Comparison, evaluation, and possible harmonisation of the HL7, DHE, and CORBA middleware
B Blobel, M Holena
New Technologies in Hospital Information Systems, 40-47, 1997
Gaussian process surrogate models for the CMA evolution strategy
L Bajer, Z Pitra, J Repický, M Holeňa
Evolutionary computation 27 (4), 665-697, 2019
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