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Authors
Advisor(s)
Abstract(s)
The agricultural output has several parts, and depending on the characteristics of the farms, one of these parcels is related to crop production. Including in the crop output, the sources of these incomes are diverse. In any case, crop production has a fundamental role in the sustainability of the farms and society, as a source of income for the farmers and food for the population. In this context, it is important to understand the main factors that may support the stakeholders in predicting the crop output in the European Union farms. The main objective of this research is to identify the most adjusted models and the most important variables to predict crop income in the European Union context. For that, data from the Farm Accountancy Data Network were considered, as well as approaches associated with artificial intelligence. The main findings provide relevant insights and knowledge, namely for farmers and policymakers that may be considered in the processes of agricultural planning, management and policy design.
Description
Keywords
Machine learning European Union databases Agricultural sector
Citation
Martinho, V.J.P.D. (2024). Applying Artificial Intelligence to Predict Crop Output. 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_2
Publisher
Springer, Cham