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A Neural Network Model for Forecasting CO2 Emission

Author

Listed:
  • Gallo, C.
  • Contò, F.
  • Fiore, M.

Abstract

Air pollution is today a serious problem, caused mainly by human activity. Classical methods are not considered able to efficiently model complex phenomena as meteorology and air pollution because, usually, they make approximations or too rigid schematisations. Our purpose is a more flexible architecture (artificial neural network model) to implement a short-term CO2 emission forecasting tool applied to the cereal sector in Apulia region – in Southern Italy - to determine how the introduction of cultural methods with less environmental impact acts on a possible pollution reduction.

Suggested Citation

  • Gallo, C. & Contò, F. & Fiore, M., 2014. "A Neural Network Model for Forecasting CO2 Emission," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 6(2), pages 1-6, June.
    • Handle: RePEc:ags:aolpei:182488
    DOI: 10.22004/ag.econ.182488
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    Cited by:

    1. Shuyu Dai & Dongxiao Niu & Yaru Han, 2018. "Forecasting of Energy-Related CO 2 Emissions in China Based on GM(1,1) and Least Squares Support Vector Machine Optimized by Modified Shuffled Frog Leaping Algorithm for Sustainability," Sustainability, MDPI, vol. 10(4), pages 1-17, March.
    2. Aysha Malik & Ejaz Hussain & Sofia Baig & Muhammad Fahim Khokhar, 2020. "Forecasting CO2 emissions from energy consumption in Pakistan under different scenarios: The China–Pakistan Economic Corridor," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 10(2), pages 380-389, April.
    3. Anh-Tu Nguyen & Shih-Hao Lu & Phuc Thanh Thien Nguyen, 2021. "Validating and Forecasting Carbon Emissions in the Framework of the Environmental Kuznets Curve: The Case of Vietnam," Energies, MDPI, vol. 14(11), pages 1-38, May.
    4. Papagera, A. & Ioannou, K. & Zaimes, G. & Iakovoglou, V. & Simeonidou, M., 2014. "Simulation and Prediction of Water Allocation Using Artificial Neural Networks and a Spatially Distributed Hydrological Model," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 6(4), pages 1-11, December.

    More about this item

    Keywords

    Environmental Economics and Policy;

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