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Forecasting Transport Emissions through Machine Learning Approaches: Insights for Sustainable Logistics

Author

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  • Ozan Ozdemir

    (Suleyman Demirel University, Isparta, Turkey)

  • Sefika Ozdemir

    (Suleyman Demirel University, Isparta, Turkey)

Abstract

No abstract is available for this item.

Suggested Citation

  • Ozan Ozdemir & Sefika Ozdemir, 2026. "Forecasting Transport Emissions through Machine Learning Approaches: Insights for Sustainable Logistics," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 28(71), pages 288-288, February.
    • Handle: RePEc:aes:amfeco:v:28:y:2026:i:71:p:288
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    References listed on IDEAS

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    5. Tao Lian & Changhao Li, 2024. "Linking Environmental Sustainability and Financial Resilience through the Environmental Footprints and Their Determinants: A Panel Data Approach for G7 Countries," Sustainability, MDPI, vol. 16(17), pages 1-17, September.
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    More about this item

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • L91 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Transportation: General
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

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