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Affenzeller, Michael
168  Ergebnisse:
Personensuche X
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1

Population Dynamics in Genetic Programming for Dynamic Symb..:

Fleck, Philipp ; Werth, Bernhard ; Affenzeller, Michael
Applied Sciences.  14 (2024)  2 - p. 596 , 2024
Link: https://doi.org/10.3390/..
 
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2

A messaging library for distributed modeling:

Zenisek, Jan ; Bachinger, Florian ; Falkner, Dominik...
Procedia Computer Science.  232 (2024)  - p. 606-615 , 2024
Link: https://doi.org/10.1016/..
 
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3

Shape-constrained Symbolic Regression: Real-World Applicati..:

, In: Genetic Programming Theory and Practice XX; Genetic and Evolutionary Computation,
Haider, Christian ; de Franca, Fabricio Olivetti ; Burlacu, Bogdan... - p. 225-240 , 2024
Link: https://doi.org/10.1007/..
 
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4

Integrating Machine Learning into Supply Chain Management:C..:

Falkner, Dominik ; Bögl, Michael ; Gattinger, Anna...
Procedia Computer Science.  232 (2024)  - p. 1779-1788 , 2024
Link: https://doi.org/10.1016/..
 
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5

Automated Machine Learning for Industrial Applications – Ch..:

Bachinger, Florian ; Zenisek, Jan ; Affenzeller, Michael
Procedia Computer Science.  232 (2024)  - p. 1701-1710 , 2024
Link: https://doi.org/10.1016/..
 
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6

Population diversity and inheritance in genetic programming..:

Burlacu, Bogdan ; Yang, Kaifeng ; Affenzeller, Michael
Natural Computing.  , 2023
Link: https://doi.org/10.1007/..
 
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7

Method of Process Optimization for LMD-Processes using Mach..:

Gröning, Holger ; Zenisek, Jan ; Wild, Norbert..
Procedia Computer Science.  217 (2023)  - p. 1506-1512 , 2023
Link: https://doi.org/10.1016/..
 
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8

Symbolic Regression in Materials Science: Discovering Inter..:

, In: Genetic and Evolutionary Computation; Genetic Programming Theory and Practice XIX,
Burlacu, Bogdan ; Kommenda, Michael ; Kronberger, Gabriel.. - p. 1-30 , 2023
Link: https://doi.org/10.1007/..
 
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9

Evolutionary Algorithms for Segment Optimization in Vectori..:

, In: Proceedings of the Companion Conference on Genetic and Evolutionary Computation,
Fleck, Philipp ; Winkler, Stephan ; Kommenda, Michael... - p. 439-442 , 2023
Link: https://dl.acm.org/doi/1..
 
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10

Implicit Directed Acyclic Graphs (DAGs) for Parallel Outlie..:

, In: IFIP Advances in Information and Communication Technology; Artificial Intelligence Applications and Innovations,
Muhr, David ; Affenzeller, Michael ; Küng, Josef - p. 3-15 , 2023
Link: https://doi.org/10.1007/..
 
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11

A New Acquisition Function for Multi-objective Bayesian Opt..:

, In: Proceedings of the Companion Conference on Genetic and Evolutionary Computation,
Yang, Kaifeng ; Chen, Kai ; Affenzeller, Michael. - p. 2308-2317 , 2023
Link: https://dl.acm.org/doi/1..
 
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12

Surrogate-assisted Multi-objective Optimization via Genetic..:

, In: Lecture Notes in Computer Science; Evolutionary Multi-Criterion Optimization,
Yang, Kaifeng ; Affenzeller, Michael - p. 176-190 , 2023
Link: https://doi.org/10.1007/..
 
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13

Gradients of Acquisition Functions for Bi-objective Bayesia..:

, In: 2023 19th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD),
Yang, Kaifeng ; Liu, Sixuan ; Affenzeller, Michael. - p. 1-9 , 2023
Link: https://doi.org/10.1109/..
 
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14

A Novel Benchmark Environment for Dynamic Factory Crane Sch..:

Karder, Johannes ; Werth, Bernhard ; Beham, Andreas..
Procedia Computer Science.  217 (2023)  - p. 1217-1224 , 2023
Link: https://doi.org/10.1016/..
 
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15

Applying Learning and Self-Adaptation to Dynamic Scheduling:

Werth, Bernhard ; Karder, Johannes ; Heckmann, Michael..
Applied Sciences.  14 (2023)  1 - p. 49 , 2023
Link: https://doi.org/10.3390/..
 
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