Maria Lucka, prof.
Maria Lucka, prof.
senior researcher, Kempelen Institute of Intelligent Technologies, Bratislava, Slovakia
Verified email at
Cited by
Cited by
Parallel ant systems for the capacitated vehicle routing problem
KF Doerner, RF Hartl, G Kiechle, M Lucka, M Reimann
European Conference on Evolutionary Computation in Combinatorial …, 2004
3D displacement finite differences and a combined memory optimization
P Moczo, M Lucká, J Kristek, M Kristeková
Bulletin of the Seismological Society of America 89 (1), 69-79, 1999
Parallel cooperative savings based ant colony optimization—multiple search and decomposition approaches
KF Doerner, RF Hartl, S Benkner, M Lucka
Parallel processing letters 16 (03), 351-369, 2006
Incremental ensemble learning for electricity load forecasting
G Grmanová, P Laurinec, V Rozinajová, AB Ezzeddine, M Lucká, P Lacko, ...
Acta Polytechnica Hungarica 13 (2), 97-117, 2016
A parallel version of the d-ant algorithm for the vehicle routing problem
KF Doerner, RF Hartl, M Lucka
Parallel Numerics 5, 109-118, 2005
Communication strategies for parallel cooperative ant colony optimization on clusters and grids
S Benkner, K Doerner, R Hartl, G Kiechle, M Lucka
Complimentary Proceedings of PARA 4, 3-12, 2004
Adaptive time series forecasting of energy consumption using optimized cluster analysis
P Laurinec, M Lóderer, P Vrablecová, M Lucká, V Rozinajová, ...
2016 IEEE 16th international conference on data mining workshops (ICDMW …, 2016
Parallel wavelet-based compression of two-dimensional data
M Lucka, T Sorevik
Proceedings of Algorithmy, 1-10, 2000
Comparison of representations of time series for clustering smart meter data
P Laurinec, M Lucká
Proceedings of the World Congress on Engineering and Computer Science 1, 2016
Interpretable multiple data streams clustering with clipped streams representation for the improvement of electricity consumption forecasting
P Laurinec, M Lucká
Data Mining and Knowledge Discovery 33 (2), 413-445, 2019
Energy load forecast using S2S deep neural networks with k-Shape clustering
T Jarábek, P Laurinec, M Lucká
2017 IEEE 14th International Scientific Conference on Informatics, 140-145, 2017
Application of multistage stochastic programs solved in parallel in portfolio management
M Lucka, I Melichercik, L Halada
Parallel Computing 34 (6-8), 469-485, 2008
Clustering-based forecasting method for individual consumers electricity load using time series representations
P Laurinec, M Lucká
Open Computer Science 8 (1), 38-50, 2018
New clustering-based forecasting method for disaggregated end-consumer electricity load using smart grid data
P Laurinec, M Lucká
2017 IEEE 14th international scientific conference on informatics, 210-215, 2017
Application of biologically inspired methods to improve adaptive ensemble learning
G Grmanová, V Rozinajová, AB Ezzedine, M Lucká, P Lacko, M Lóderer, ...
Advances in Nature and Biologically Inspired Computing, 235-246, 2016
Parallelization strategies of three-stage stochastic program based on the BQ method
S Benkner, L Halada, M Lucka
Using biologically inspired computing to effectively improve prediction models
AB Ezzeddine, M Lóderer, P Laurinec, P Vrablecová, V Rozinajová, ...
International Journal of Hybrid Intelligent Systems 13 (2), 99-112, 2016
Density-based unsupervised ensemble learning methods for time series forecasting of aggregated or clustered electricity consumption
P Laurinec, M Lóderer, M Lucká, V Rozinajová
Journal of Intelligent Information Systems 53 (2), 219-239, 2019
Usefulness of unsupervised ensemble learning methods for time series forecasting of aggregated or clustered load
P Laurinec, M Lucká
International Workshop on New Frontiers in Mining Complex Patterns, 122-137, 2017
Parallel posix threads based ant colony optimization using asynchronous communication
M Lucka, S Piecka
Proceedings of the 8th International Conference on Applied Mathematics 2 …, 2009
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