Abstract
Consumption of fossil energy resources were increased dramatically, due to the economic and population growth. In turn, the consumption of fossil resources causes depletion of resources and contributes to environmental pollution. The European Union's "climate neutrality" initiative requires effective energy management from the member states. By this is meant a resource-efficient and competitive economy in which there is no greenhouse gas emission and where economic growth is decoupled from resource consumption. The article analyzes the level of primary energy consumption in Poland. It was examined whether a 23% drop in energy consumption could be achieved in 2030 compared to the base year and according with energy efficiency assumptions. A methodology for forecasting primary energy consumption based on deep neural networks, in particular on Long Short Term Memory (LSTM) algorithms was also presented.
| Translated title of the contribution | Analiza i prognozowanie zużycia energii pierwotnej w Polsce z wykorzystaniem technik głębokiego uczenia |
|---|---|
| Original language | English |
| Pages (from-to) | 217-222 |
| Number of pages | 6 |
| Journal | Inzynieria Mineralna |
| Volume | 2020 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 8 Decent Work and Economic Growth
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SDG 12 Responsible Consumption and Production
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SDG 13 Climate Action
Keywords
- Deep learning methods
- Deep neural network
- Long short-term memory
- Primary energy consumption
ASJC Scopus subject areas
- Geotechnical Engineering and Engineering Geology
- Geochemistry and Petrology
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