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Risks of Agricultural Economy and Climate Risk Management for Enterprises of Agriculture 4.0 Based on Deep Learning

In: Food Security in the Economy of the Future

Author

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  • Tatiana N. Litvinova

    (Volgograd State Agricultural University)

Abstract

The paper investigates the climate risks of the agricultural economy and justifies the benefits of risk management of enterprises in agriculture 4.0 based on deep learning. To achieve the research purpose, the authors apply the regression analysis method, which models the dependence of food security indicators on the management of climate risks in agriculture in 2021. Using the resulting model, the authors determine the maximum possible potential increase in the values of food security indicators through the management of climate risks in digital agriculture. The authors conduct a comparative analysis of the risk management of agricultural enterprises in digital agriculture and agriculture 4.0. The research results reveal the limitations of digital agriculture, with climate risk management of the agricultural economy improving but not fully ensuring food security. Prospects for risk management are related to the development of agriculture 4.0 based on deep learning, the benefits of which are systemic, preventive, more flexible, rational, and effective management of climate risks in the agricultural economy. The research forms the scientific and methodological basis for improving the climate risk management of the agricultural economy based on agriculture 4.0 based on advanced deep learning technology.

Suggested Citation

  • Tatiana N. Litvinova, 2023. "Risks of Agricultural Economy and Climate Risk Management for Enterprises of Agriculture 4.0 Based on Deep Learning," Springer Books, in: Elena G. Popkova & Bruno S. Sergi (ed.), Food Security in the Economy of the Future, chapter 0, pages 93-99, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-23511-5_10
    DOI: 10.1007/978-3-031-23511-5_10
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