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Authors
Advisor(s)
Abstract(s)
It is not expected that the agricultural sector absorbs a great part of the employment in developed economies with a dynamic industry and services sector. When the percentage of employment in agriculture is high, this may be a sign of the weak performance of the farms. Every country wants to have a developed farming sector to not compromise the dynamics and performance of the economy. In any case, agricultural employment plays a fundamental role, particularly in rural spaces and in contexts of temporary crises in the remaining economy. Taking into account these motivations, this chapter aims to highlight the main approaches and variables that may be considered to predict labour use in the European Union farms. To achieve these aims, European Union agricultural statistics were considered, as well as models based on the new technologies associated with the digital transition worldwide. The results found may provide pertinent suggestions for a more sustainable farming sector, where the social contributions may be improved.
Description
Keywords
Accuracy European Union farm accountancy data network Agricultural employment
Citation
Martinho, V.J.P.D. (2024). Predictive Artificial Intelligence Approaches of Labour Use in the Farming Sector. In: Machine Learning Approaches for Evaluating Statistical Information in the Agricultural Sector. SpringerBriefs in Applied Sciences and Technology. Springer, Cham. https://doi.org/10.1007/978-3-031-54608-2_10
Publisher
Springer, Cham