Abstract

Greenhouse gas emissions (GHG) generated by human activities have negative impacts such as climate change, global warming, threats to food security, natural disasters, and rising sea levels. Several countries have implemented measures to reduce GHG emissions, including reforestation, environmentally friendly industries, and providing incentives to initiatives that reduce GHG emissions. A carbon price prediction is provided to optimize carbon incentives for investors. Carbon price fluctuation on global market conditions requires methods to predict the prices accurately. The methods utilize carbon price data from European Energy Exchange (EEX) carbon market. The data employed in this research encompasses the closing prices of carbon. This research applies two algorithms, Deep Multilayer Perceptron (DMLP) and Long Short-Term Memory (LSTM), to forecast carbon prices in time series predictions. These models use the closing price variable. The simulation results show that the Deep Multilayer Perceptron method is more accurate than the Long Short-Term Memory method. The method with higher performance will result in better risk measurement of carbon price.

Original languageEnglish
Title of host publicationProceeding - EECSI 2023
Subtitle of host publication10th Electrical Engineering, Computer Science and Informatics Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages307-314
Number of pages8
ISBN (Electronic)9798350306866
DOIs
Publication statusPublished - 2023
Event10th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2023 - Palembang, Indonesia
Duration: 20 Sept 202321 Sept 2023

Publication series

NameInternational Conference on Electrical Engineering, Computer Science and Informatics (EECSI)
ISSN (Print)2407-439X

Conference

Conference10th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2023
Country/TerritoryIndonesia
CityPalembang
Period20/09/2321/09/23

Keywords

  • Greenhouse gas emissions
  • carbon market
  • carbon price
  • deep multilayer perceptron
  • long short-term memory

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