Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/87987

TítuloMeteorological time series: an exploratory statistical and critical analysis
Autor(es)Gonçalves, A. Manuela
Pereira, F. Catarina
Costa, Marco
Leão, Celina Pinto
Palavras-chaveExploratory data analysis
Imputation
Irrigation
Meteorological variables
Time series
Data2023
EditoraSpringer Nature
RevistaLecture Notes in Mechanical Engineering
Resumo(s)Increasingly, reduction of water availability has been a reality, and population growth, pollution, and climate change have contributed to exacerbating this problem. Dry periods, which occur when precipitation is lower than expected in a given territory, have become more frequent and prolonged, and therefore it is crucial to efficiently manage water use in response to environmental concerns. The main challenge in this work is to present the irrigation problem as an optimal control problem along with the presentation of preliminary results based on an exploratory statistical and critical analysis of daily meteorological variables. The variables considered are: maximum air temperature, minimum air temperature, and total precipitation recorded during the last ten years (2010–2019). The methodology followed, based on state-space models, shows flexibility to allow the integration of new data, updating in real time the model, and the incorporation of covariates that are important to explain the process in analysis.
TipoArtigo em ata de conferência
URIhttps://hdl.handle.net/1822/87987
ISBN978-3-031-09359-3
e-ISBN978-3-031-09360-9
DOI10.1007/978-3-031-09360-9_17
ISSN2195-4356
Versão da editorahttps://link.springer.com/chapter/10.1007/978-3-031-09360-9_17
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:CMAT - Artigos em atas de conferências e capítulos de livros com arbitragem / Papers in proceedings of conferences and book chapters with peer review

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