Repository logo
 
Publication

The Most Adjusted Predictive Models for Energy Costs

2024Book part Restricted access
Simple item page
dc.contributor.authorMartinho, Vítor
dc.date.accessioned2024-11-12T14:00:12Z
dc.date.available2024-11-12T14:00:12Z
dc.date.issued2024
dc.description.abstractEnergy is one of the most important production factors in farms, considering its impact on the profitability of the agricultural sector, its relationship with sustainability and the need for a green transition in agriculture to deal with the challenges created by climate change and the consequent global warming. In the green transition, it is important to replace fossil fuel sources with renewable energies and, in these contexts, the agricultural sector may make a double contribution, producing renewable energy and using more sustainable sources for the different processes and activities in the farms. Taking into account these motivations, this chapter proposes to select the models with better accuracy and the most relevant variables to predict the energy costs in the European Union farming sector. For that, machine learning models were considered, as well as statistical information from European Union databases. This chapter presents useful contributions to better understand the contexts associated with energy cost prediction in European farms.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationMartinho, V.J.P.D. (2024). The Most Adjusted Predictive Models for Energy Costs. 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_7pt_PT
dc.identifier.doi10.1007/978-3-031-54608-2_7pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.19/8633
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer, Champt_PT
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-031-54608-2_7pt_PT
dc.subjectDigital Era approachespt_PT
dc.subjectPredictorspt_PT
dc.subjectEuropean Unionpt_PT
dc.titleThe Most Adjusted Predictive Models for Energy Costspt_PT
dc.typebook part
dspace.entity.typePublication
oaire.citation.endPage97pt_PT
oaire.citation.startPage87pt_PT
person.familyNamePereira Domingues Martinho
person.givenNameVítor João
person.identifier.ciencia-idF510-903F-51FA
rcaap.rightsclosedAccesspt_PT
rcaap.typebookPartpt_PT
relation.isAuthorOfPublicationd99fa017-5c04-4606-b382-f069996da23f
relation.isAuthorOfPublication.latestForDiscoveryd99fa017-5c04-4606-b382-f069996da23f

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
32569ec2-8502-4a1c-87e2-ae82b7138bb6 (Versão publicada).pdf
Size:
4.86 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.79 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

CERNAS - Capítulo em obra internacional, como autor
ESAV - DEAS - Capítulo em obra internacional, como autor