Machine learning approaches for evaluating statistical information in the agricultural sector / Vitor Joao Pereira Domingues Martinho.
This book presents machine learning approaches to identify the most important predictors of crucial variables for dealing with the challenges of managing production units and designing agriculture policies. The book focuses on the agricultural sector in the European Union and considers statistical i...
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Full Text (via Springer) |
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| Format: | eBook |
| Language: | English |
| Published: |
Cham, Switzerland :
Springer,
[2024]
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| Series: | SpringerBriefs in applied sciences and technology.
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Table of Contents:
- 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 Unions agricultural sector
- Chapter 10. Predictive artificial intelligence approaches of labour use in the farming sector.