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Economic Growth: Advances in Analysis Methodologies and Technologies [[electronic resource] /] / by Vitor Joao Pereira Domingues Martinho
| Economic Growth: Advances in Analysis Methodologies and Technologies [[electronic resource] /] / by Vitor Joao Pereira Domingues Martinho |
| Autore | Martinho Vitor Joao Pereira Domingues |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (XIII, 144 p. 41 illus., 40 illus. in color.) |
| Disciplina | 338.9 |
| Collana | SpringerBriefs in Applied Sciences and Technology |
| Soggetto topico |
Economic development
Power resources Environmental economics Econometrics Sustainability Economic Growth Resource and Environmental Economics Quantitative Economics Natural Resource and Energy Economics |
| ISBN | 3-031-38363-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1: Economic growth: Sigma and beta convergence processes worldwide -- Chapter 2: Clubs of convergence: Insights from the main groups of countries -- Chapter 3: World trends: Differences and similitudes between absolute and conditional convergence -- Chapter 4: Constant, decreasing, or increasing returns to scale: Evidence from the Verdoorn and Kaldor laws -- Chapter 5: Circular and cumulative processes in economic growth: The importance of the external demand -- Chapter 6: Interrelationships between economic growth and sustainability: Highlights from the literature -- Chapter 7: Sustainable development: Contributions from life cycle cost analysis -- Chapter 8: Social life cycle assessment: Relationships with the economic growth -- Chapter 9: Machine and deep learning: Their roles in the context of the economic growth processes and sustainability assessment -- Chapter 10: Economic growth, sustainability assessment and artificial intelligence: Combinations among these three dimensions. |
| Record Nr. | UNINA-9910736987703321 |
Martinho Vitor Joao Pereira Domingues
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning Approaches for Evaluating Statistical Information in the Agricultural Sector [[electronic resource] /] / by Vitor Joao Pereira Domingues Martinho
| Machine Learning Approaches for Evaluating Statistical Information in the Agricultural Sector [[electronic resource] /] / by Vitor Joao Pereira Domingues Martinho |
| Autore | Martinho Vitor Joao Pereira Domingues |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (138 pages) |
| Disciplina | 006.31 |
| Collana | SpringerBriefs in Applied Sciences and Technology |
| Soggetto topico |
Machine learning
Production management Agriculture - Economic aspects Power resources Environmental economics Machine Learning Production Agricultural Economics Resource and Environmental Economics |
| ISBN | 3-031-54608-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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. |
| Record Nr. | UNINA-9910841869303321 |
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Martinho Vitor Joao Pereira Domingues
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||