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DC Field | Value | Language |
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dc.contributor.author | Costa, Cláudia | pt_PT |
dc.contributor.author | Gonçalves, A. Manuela | pt_PT |
dc.contributor.author | Costa, Marco | pt_PT |
dc.contributor.author | Lopes, Sofia O. | pt_PT |
dc.date.accessioned | 2019-08-27T14:50:44Z | - |
dc.date.available | 2019-08-27T14:50:44Z | - |
dc.date.issued | 2019-07 | - |
dc.identifier.uri | http://hdl.handle.net/10773/26437 | - |
dc.description.abstract | Climate change is a reality and efficient use of scarce resources is vital. The challenge of this project is to study the behaviour of humidity in the soil by mathematical/statistical modeling in order to find optimal solutions to improve the efficiency of daily water use in irrigation systems. For that, it is necessary to estimate and forecast weather variables, in this particular case daily maximum and minimum air temperature. These time series present strong trend and high- frequency seasonality. This way, we perform a state space modeling framework using exponential smoothing by incorporating Box-Cox transformations, ARMA residuals, Trend and Seasonality. | pt_PT |
dc.description.sponsorship | This research was partially financed by Portuguese funds by the Center for Research and Development in Mathematics and Applications (CIDMA) and the Portuguese Foundation for Science and Technology (”Fundação para a Ciência e a Tecnologia” - FCT), within project UID/MAT/04106 2019. This research was partially financed by Portuguese funds through Portuguese Foundation for Science and Technology (”Fundação para a Ciência e a Tecnologia” - FCT), within project UID/MAT/00013/2013. FEDER/ COMPETE/- NORTE2020/ POCI/FCT funds through grants PTDC-EEI-AUT-2933-2014116858-TOCCATA and To CHAIR - POCI-01-0145-FEDER-028247 Financial support from the Portuguese Foundation for Science and Technology (FCT) within the framework of Strategic Financing UIDIFIS/04650/2013 is also acknowledged. | pt_PT |
dc.language.iso | eng | pt_PT |
dc.publisher | IWSM2019 | pt_PT |
dc.relation | POCI-01-0145-FEDER-028247 | pt_PT |
dc.relation | UID/MAT/04106 2019 | pt_PT |
dc.relation | info:eu-repo/grantAgreement/FCT/5876/147370/PT | pt_PT |
dc.rights | openAccess | pt_PT |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | pt_PT |
dc.subject | Forecasting | pt_PT |
dc.subject | Irrigation | pt_PT |
dc.subject | TBATS | pt_PT |
dc.subject | Temperature | pt_PT |
dc.subject | Time Series Modeling | pt_PT |
dc.title | Forecasting temperature time series for irrigation planning problems | pt_PT |
dc.type | conferenceObject | pt_PT |
dc.description.version | published | pt_PT |
dc.peerreviewed | yes | pt_PT |
ua.event.date | 7-12 Julho, 2019 | pt_PT |
degois.publication.location | Guimarães | pt_PT |
degois.publication.title | 34th International Workshop on Statistical Modelling (IWSM 2019) | pt_PT |
dc.relation.publisherversion | http://www.iwsm2019.org/ | pt_PT |
Appears in Collections: | CIDMA - Comunicações DMat - Comunicações ESTGA - Comunicações PSG - Comunicações |
Files in This Item:
File | Description | Size | Format | |
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Forecasting Temperature Time Series for Irrigation Planning Problems IWSM2019.pdf | 487.58 kB | Adobe PDF | View/Open |
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