| Autor: |
Kazolis Dimitrios Th., Kogias Panagiotis G., Roumeliotis Nikolaos I. |
| Jazyk: |
English<br />French |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
E3S Web of Conferences, Vol 404, p 01005 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2267-1242 |
| DOI: |
10.1051/e3sconf/202340401005 |
| Popis: |
The main aim of this effort is the discovery of knowledge from data, concerning consumption of electric energy, during the year 2022, based on unattended learning methods. These data were collected from the Public Electricity Company of Kavala and the methods used are, at first the Factor analysis and second the K-means clustering algorithm. The overhead methodologies are realized by the use of Statistica Data Miner software. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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