Machine Learning Approaches for Evaluating Statistical Information in the Agricultural Sector
Machine Learning Approaches for Evaluating Statistical Information in the Agricultural Sector
Martinho, Vitor Joao Pereira Domingues
Springer International Publishing AG
02/2024
135
Mole
Inglês
9783031546075
15 a 20 dias
Descrição não disponível.
Chapter 1. Predictive machine learning approaches to agricultural output.- Chapter 2. Applying artificial intelligence to predict crops output.- Chapter 3. Predictive machine learning models for livestock output.- Chapter 4. Predicting the total costs of production factors on farms in the European Union.- Chapter 5. The most important predictors of fertiliser costs.- Chapter 6. Important indicators for predicting crop protection costs.- Chapter 7. The most adjusted predictive models for energy costs.- Chapter 8. Machine learning methodologies, wages paid and the most relevant predictors.- Chapter 9. Predictors of interest paid in the European Union's agricultural sector.- Chapter 10. Predictive artificial intelligence approaches of labour use in the farming sector.
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Farm Accountancy Data Network;European Union Farms;Common Agricultural Policy;Machine Learning Approaches;Econometric Methodologies;Agricultural Economics and Policies
Chapter 1. Predictive machine learning approaches to agricultural output.- Chapter 2. Applying artificial intelligence to predict crops output.- Chapter 3. Predictive machine learning models for livestock output.- Chapter 4. Predicting the total costs of production factors on farms in the European Union.- Chapter 5. The most important predictors of fertiliser costs.- Chapter 6. Important indicators for predicting crop protection costs.- Chapter 7. The most adjusted predictive models for energy costs.- Chapter 8. Machine learning methodologies, wages paid and the most relevant predictors.- Chapter 9. Predictors of interest paid in the European Union's agricultural sector.- Chapter 10. Predictive artificial intelligence approaches of labour use in the farming sector.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.