CO2 emission modeling of countries in Southeast of Europe by using artificial neural network

Nawaf Ali; Mamdouh El Haj Assad; Habib Forootan Fard; Babak Amani Jourdehi; Ibrahim Mahariq; Mohammad A. AlShabi

doi:10.1117/12.2632641

1 June 2022 CO₂ emission modeling of countries in Southeast of Europe by using artificial neural network

Nawaf Ali, Mamdouh El Haj Assad, Habib Forootan Fard, Babak Amani Jourdehi, Ibrahim Mahariq, Mohammad A. AlShabi

Proceedings Volume 12120, Sensing for Agriculture and Food Quality and Safety XIV; 121200F (2022) https://doi.org/10.1117/12.2632641
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

Emission of greenhouse gases such as CO₂ is highly dependent on the energy systems of the countries. In this regard, for accurate analysis of CO₂emission it is necessary to take into account the factors related to energy consumption. In the present paper, three countries including Turkey, Bulgaria and Greece are considered as case studies to model their CO₂ by using an economic indicator (GDP) and consumptions of different energy sources. In this regard, Group Method of Data Handling (GMDH) is applied as the method and the required data for modeling between 2000 and 2019 are gathered. The results indicated that R² values of the proposed model for training, test and overall datasets are 0.9997, 0.9991 and 0.9995, respectively. In addition, AARD of the mentioned datasets were around 0.71%, 1.18% and 0.85%, respectively. These values reveal significant exactness of the proposed which can be attributed to proper selection of both inputs and modeling method.

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Citation Download Citation

Nawaf Ali, Mamdouh El Haj Assad, Habib Forootan Fard, Babak Amani Jourdehi, Ibrahim Mahariq, and Mohammad A. AlShabi "CO₂ emission modeling of countries in Southeast of Europe by using artificial neural network", Proc. SPIE 12120, Sensing for Agriculture and Food Quality and Safety XIV, 121200F (1 June 2022); https://doi.org/10.1117/12.2632641

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