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

Tatiana N. Litvinova ()
Additional contact information
Tatiana N. Litvinova: Volgograd State Agricultural University

Chapter Chapter 10 in Food Security in the Economy of the Future, 2023, pp 93-99 from Springer

Abstract: 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.

Keywords: Risks of agricultural economy; Climate risk management; Agricultural enterprises; Agriculture 4.0; Deep learning; D81; G32; Q54; L26; O13 (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-23511-5_10

Ordering information: This item can be ordered from
http://www.springer.com/9783031235115

DOI: 10.1007/978-3-031-23511-5_10

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().