Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: International Conference on Business Information Systems
Год издания: 2022
Идентификатор DOI: 10.1007/978-3-031-04216-4_1
Ключевые слова: clustering, energy, germany, intellectual analysis, kohonen maps, neural networks
Аннотация: The purpose of the research in this article is to analyze the structure of energy in Germany and compare the obtained data with events occurring in the country and the world. The article reviews the world energy sector and considers the rating of regions by gross energy production. The analysis helps to identify the leading regionsПоказать полностьюin terms of energy production: Asia and Oceania, North America and Europe. The German economy and energy sector were considered, as well as the development of nuclear power in particular and the gradual abandonment from nuclear power plants because of the occurred radiation accidents in the world. It also describes the relevance of data analysis in the energy sector, especially in working with renewable energy sources due to their instability and unpredictability. Using self-organizing Kohonen maps, the data on German energy indicators was analyzed. Basing on the analysis it was concluded that these maps correspond to the changes in the energy policy of Germany. © 2022, Springer Nature Switzerland AG.
Журнал: Lecture Notes in Business Information Processing
Выпуск журнала: Vol. 444 LNBIP
Номера страниц: 5-13
ISSN журнала: 18651348
Издатель: Springer Science and Business Media Deutschland GmbH