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Peter Laurinec
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2010 – 2019
- 2019
- [j5]Peter Laurinec
, Mária Lucká:
Interpretable multiple data streams clustering with clipped streams representation for the improvement of electricity consumption forecasting. Data Min. Knowl. Discov. 33(2): 413-445 (2019) - [j4]Peter Laurinec
Density-based unsupervised ensemble learning methods for time series forecasting of aggregated or clustered electricity consumption. J. Intell. Inf. Syst. 53(2): 219-239 (2019) - 2018
- [j3]Peter Laurinec
Clustering-based forecasting method for individual consumers electricity load using time series representations. Open Comput. Sci. 8(1): 38-50 (2018) - [j2]Peter Laurinec
TSrepr R package: Time Series Representations. J. Open Source Softw. 3(23): 577 (2018) - [c4]Peter Laurinec
Application of Parallel Genetic Algorithm for Model-Based Gaussian Cluster Analysis. IBICA 2018: 140-150 - 2017
- [c3]Peter Laurinec
Usefulness of Unsupervised Ensemble Learning Methods for Time Series Forecasting of Aggregated or Clustered Load. NFMCP@PKDD/ECML 2017: 122-137 - 2016
- [j1]Anna Bou Ezzeddine, Marek Lóderer, Peter Laurinec
Using biologically inspired computing to effectively improve prediction models. Int. J. Hybrid Intell. Syst. 13(2): 99-112 (2016) - [c2]Peter Laurinec
Adaptive Time Series Forecasting of Energy Consumption Using Optimized Cluster Analysis. ICDM Workshops 2016: 398-405 - 2015
- [c1]Gabriela Grmanová
Application of Biologically Inspired Methods to Improve Adaptive Ensemble Learning. NaBIC 2015: 235-246
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