Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Marek Loderer"'
Publikováno v:
Journal of Intelligent Information Systems. 53:219-239
This paper presents a comparison of the impact of various unsupervised ensemble learning methods on electricity load forecasting. The electricity load from consumers is simply aggregated or optimally clustered to more predictable groups by cluster an
Publikováno v:
Acta Polytechnica Hungarica. 15:199-216
Autor:
Viera Rozinajová, Marek Loderer, Pavol Podhradsky, Gregor Rozinaj, Marek Vanco, Gabriel-Miro Muntean
Publikováno v:
2019 International Symposium ELMAR.
This paper presents an innovative project in the field of education, which applies modern graphic technologies, such as virtual and augmented reality. The project consists of multiple applications, which are using various technologies for different l
Publikováno v:
Intelligent Data Engineering and Automated Learning – IDEAL 2019 ISBN: 9783030336066
IDEAL (1)
IDEAL (1)
Nowadays, the electricity load profiles of customers (consumers and prosumers) are changing as new technologies are being developed, and therefore it is necessary to correctly identify new trends, changes and anomalies in data. Anomalies in load cons
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9645d4989d60ff3107f5db4f184933f1
https://doi.org/10.1007/978-3-030-33607-3_50
https://doi.org/10.1007/978-3-030-33607-3_50
Autor:
Peter Laurinec, Gabriela Grmanová, Mária Lucká, Marek Loderer, Petra Vrablecová, Viera Rozinajová, Anna Bou Ezzeddine, Peter Lacko
Publikováno v:
International Journal of Hybrid Intelligent Systems. 13:99-112
The complexity of certain problems causes that classical methods for finding exact solutions have some limitations. In this paper we propose an incremental heterogeneous ensemble model for time series prediction where biologically inspired algorithms
Publikováno v:
Intelligent Data Engineering and Automated Learning – IDEAL 2018 ISBN: 9783030034924
IDEAL (1)
IDEAL (1)
In this paper, we explore how the modified Dynamic Weighted Majority (DWM) method of ensemble learning can enhance time series prediction. DWM approach was originally introduced as a method to combine predictions of multiple classifiers. In our appro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b6a469c0cefd7b665af0d84d7be9215
https://doi.org/10.1007/978-3-030-03493-1_68
https://doi.org/10.1007/978-3-030-03493-1_68
Autor:
Petra Vrablecová, Róbert Magyar, Anna Bou Ezzeddine, Viera Rozinajová, Jaroslav Loebl, Marek Loderer
This chapter presents one way of incorporating computational intelligence into smart grid environment. We introduce an energy ecosystem, where contemporary technologies are used and by involving advanced methods of data analysis and optimization, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aceaf3512fa2bd672dcc491dcb0027d2
https://doi.org/10.1016/b978-0-12-813314-9.00002-5
https://doi.org/10.1016/b978-0-12-813314-9.00002-5
Publikováno v:
2017 IEEE 14th International Scientific Conference on Informatics.
Prediction of electricity consumption has become a very investigated field of research recently. By lowering prediction error, we can minimize costs of suppliers. The classical approach using one prediction model has been proved insufficient. The pro
Autor:
Peter Laurinec, Petra Vrablecová, Viera Rozinajová, Mária Lucká, Marek Loderer, Anna Bou Ezzeddine
Publikováno v:
ICDM Workshops
The paper presents an improvement of incremental adaptive power load forecasting methods by performing cluster analysis prior to forecasts. For clustering the centroid based method K-means, with K-means++ centroids initialization, was used. Ten vario
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783319489438
The paper deals with the prediction of electricity demand, using data from smart meters obtained in defined time steps. We propose the modification of ensemble learning method called Dynamic Weighted Majority (DWM). The data are represented by data s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a3113905d9efc5fb14ec208bc53aae4
https://doi.org/10.1007/978-3-319-48944-5_4
https://doi.org/10.1007/978-3-319-48944-5_4