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Analysis and Forecasting of the Primary Energy Consumption in Poland Using Deep Learning

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

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 contributionAnaliza i prognozowanie zużycia energii pierwotnej w Polsce z wykorzystaniem technik głębokiego uczenia
Original languageEnglish
Pages (from-to)217-222
Number of pages6
JournalInzynieria Mineralna
Volume2020
Issue number1
DOIs
Publication statusPublished - 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  3. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  4. SDG 13 - Climate Action
    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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