Forecasting Multiple Groundwater Time Series with Local and Global Deep Learning Networks
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Montero-Manso, Pablo & Hyndman, Rob J., 2021.
"Principles and algorithms for forecasting groups of time series: Locality and globality,"
International Journal of Forecasting, Elsevier, vol. 37(4), pages 1632-1653.
- Pablo Montero-Manso & Rob J Hyndman, 2020. "Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globality," Monash Econometrics and Business Statistics Working Papers 45/20, Monash University, Department of Econometrics and Business Statistics.
- Markus Reichstein & Gustau Camps-Valls & Bjorn Stevens & Martin Jung & Joachim Denzler & Nuno Carvalhais & Prabhat, 2019. "Deep learning and process understanding for data-driven Earth system science," Nature, Nature, vol. 566(7743), pages 195-204, February.
- Durbin, James & Koopman, Siem Jan, 2012.
"Time Series Analysis by State Space Methods,"
OUP Catalogue,
Oxford University Press,
edition 2, number 9780199641178.
- Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
- Tom Doan, "undated". "SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM," Statistical Software Components RTS00251, Boston College Department of Economics.
- Wehrens, Ron & Buydens, Lutgarde M. C., 2007. "Self- and Super-organizing Maps in R: The kohonen Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 21(i05).
- Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2022. "M5 accuracy competition: Results, findings, and conclusions," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1346-1364.
- Stephanie Clark & Rob J. Hyndman & Dan Pagendam & Louise M. Ryan, 2020. "Modern Strategies for Time Series Regression," International Statistical Review, International Statistical Institute, vol. 88(S1), pages 179-204, December.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Guobin Fu & Stephanie R. Clark & Dennis Gonzalez & Rodrigo Rojas & Sreekanth Janardhanan, 2023. "Spatial and Temporal Patterns of Groundwater Levels: A Case Study of Alluvial Aquifers in the Murray–Darling Basin, Australia," Sustainability, MDPI, vol. 15(23), pages 1-18, November.
- Stephen Afrifa & Tao Zhang & Peter Appiahene & Vijayakumar Varadarajan, 2022. "Mathematical and Machine Learning Models for Groundwater Level Changes: A Systematic Review and Bibliographic Analysis," Future Internet, MDPI, vol. 14(9), pages 1-31, August.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Wellens, Arnoud P. & Boute, Robert N. & Udenio, Maximiliano, 2024. "Simplifying tree-based methods for retail sales forecasting with explanatory variables," European Journal of Operational Research, Elsevier, vol. 314(2), pages 523-539.
- Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022.
"Forecasting: theory and practice,"
International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
- Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
- Fildes, Robert & Kolassa, Stephan & Ma, Shaohui, 2022. "Post-script—Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1319-1324.
- Avanzi, Benjamin & Taylor, Greg & Vu, Phuong Anh & Wong, Bernard, 2020. "A multivariate evolutionary generalised linear model framework with adaptive estimation for claims reserving," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 50-71.
- François R. Velde, 2009.
"Chronicle of a Deflation Unforetold,"
Journal of Political Economy, University of Chicago Press, vol. 117(4), pages 591-634, August.
- Francois R. Velde, 2006. "Chronicles of a deflation unforetold," Working Paper Series WP-06-12, Federal Reserve Bank of Chicago.
- Wen Xu, 2016. "Estimation of Dynamic Panel Data Models with Stochastic Volatility Using Particle Filters," Econometrics, MDPI, vol. 4(4), pages 1-13, October.
- Alejandro Rodriguez & Esther Ruiz, 2009.
"Bootstrap prediction intervals in state–space models,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 30(2), pages 167-178, March.
- Rodríguez, Alejandro, 2008. "Bootstrap prediction intervals in State Space models," DES - Working Papers. Statistics and Econometrics. WS ws081104, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Parrini, Alessandro, 2013. "Importance Sampling for Portfolio Credit Risk in Factor Copula Models," MPRA Paper 103745, University Library of Munich, Germany.
- Jean-Luc Gaffard, 2014.
"Crise de la théorie et crise de la politique économique. Des modèles d'équilibre général stochastique aux modèles de dynamique hors de l'équilibre,"
Revue économique, Presses de Sciences-Po, vol. 65(1), pages 71-96.
- Jean-Luc Gaffard, 2012. "Crise de la théorie et crise de la politique économique : des modèles d'équilibre général stochastique aux modèles de dynamique hors de l'équilibre," SciencePo Working papers Main hal-01070291, HAL.
- Jean-Luc Gaffard, 2014. "Crise de la théorie et crise de la politique économique : des modèles d'équilibre général stochastique aux modèles de dynamique hors de l'équilibre," SciencePo Working papers Main halshs-00931247, HAL.
- Jean-Luc Gaffard, 2014. "Crise de la théorie et crise de la politique économique : des modèles d'équilibre général stochastique aux modèles de dynamique hors de l'équilibre," Post-Print halshs-00931247, HAL.
- Jean Luc Gaffard, 2012. "Crise de la theorie et crise de la politique économique : des modèles d'équilibre général stochastique aux modèles de dynamique hors de l'équilibre," Documents de Travail de l'OFCE 2012-10, Observatoire Francais des Conjonctures Economiques (OFCE).
- Jean-Luc Gaffard, 2012. "Crise de la théorie et crise de la politique économique : des modèles d'équilibre général stochastique aux modèles de dynamique hors de l'équilibre," Working Papers hal-01070291, HAL.
- Salman Huseynov, 2021. "Long and short memory in dynamic term structure models," CREATES Research Papers 2021-15, Department of Economics and Business Economics, Aarhus University.
- Tsionas, Mike G., 2021. "Bayesian forecasting with the structural damped trend model," International Journal of Production Economics, Elsevier, vol. 234(C).
- Tommaso Proietti, 2002.
"Some Reflections on Trend-Cycle Decompositions with Correlated Components,"
Econometrics
0209002, University Library of Munich, Germany.
- Tommaso PROIETTI, 2002. "Some Reflections on Trend-Cycle Decompositions with Correlated Components," Economics Working Papers ECO2002/23, European University Institute.
- Tobias Hartl & Roland Jucknewitz, 2022.
"Approximate state space modelling of unobserved fractional components,"
Econometric Reviews, Taylor & Francis Journals, vol. 41(1), pages 75-98, January.
- Tobias Hartl & Roland Weigand, 2018. "Approximate State Space Modelling of Unobserved Fractional Components," Papers 1812.09142, arXiv.org, revised May 2020.
- Broto Carmen & Ruiz Esther, 2009.
"Testing for Conditional Heteroscedasticity in the Components of Inflation,"
Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(2), pages 1-30, May.
- Carmen Broto & Esther Ruiz, 2008. "Testing for conditional heteroscedasticity in the components of inflation," Working Papers 0812, Banco de España.
- Marczak, Martyna & Proietti, Tommaso, 2016.
"Outlier detection in structural time series models: The indicator saturation approach,"
International Journal of Forecasting, Elsevier, vol. 32(1), pages 180-202.
- Martyna Marczak & Tommaso Proietti, 2014. "Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach," CREATES Research Papers 2014-20, Department of Economics and Business Economics, Aarhus University.
- Marczak, Martyna & Proietti, Tommaso, 2015. "Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113137, Verein für Socialpolitik / German Economic Association.
- Marczak, Martyna & Proietti, Tommaso, 2014. "Outlier detection in structural time series models: The indicator saturation approach," FZID Discussion Papers 90-2014, University of Hohenheim, Center for Research on Innovation and Services (FZID).
- Martyna Marczak & Tommaso Proietti, 2014. "Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach," CEIS Research Paper 325, Tor Vergata University, CEIS, revised 08 Aug 2014.
- Oreste Napolitano & Alberto Montagnoli, 2010. "The European Unemployment Gap and the Role of Monetary Policy," Economics Bulletin, AccessEcon, vol. 30(2), pages 1346-1358.
- Licheng Liu & Wang Zhou & Kaiyu Guan & Bin Peng & Shaoming Xu & Jinyun Tang & Qing Zhu & Jessica Till & Xiaowei Jia & Chongya Jiang & Sheng Wang & Ziqi Qin & Hui Kong & Robert Grant & Symon Mezbahuddi, 2024. "Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
- Joshua Chan & Arnaud Doucet & Roberto León-González & Rodney W. Strachan, 2018.
"Multivariate Stochastic Volatility with Co-Heteroscedasticity,"
Working Paper series
18-38, Rimini Centre for Economic Analysis.
- Joshua Chan & Arnaud Doucet & Roberto Leon-Gonzalez & Rodney W. Strachan, 2018. "Multivariate Stochastic Volatility with Co-Heteroscedasticity," GRIPS Discussion Papers 18-12, National Graduate Institute for Policy Studies.
- Joshua Chan & Arnaud Doucet & Roberto León-González & Rodney W. Strachan, 2018. "Multivariate stochastic volatility with co-heteroscedasticity," CAMA Working Papers 2018-52, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- CHAN Joshua & DOUCET Arnaud & Roberto Leon-Gonzalez & STRACHAN Rodney W., 2020. "Multivariate Stochastic Volatility with Co-Heteroscedasticity," GRIPS Discussion Papers 20-09, National Graduate Institute for Policy Studies.
- Siem Jan Koopman & Joao Valle e Azevedo, 2003. "Measuring Synchronisation and Convergence of Business Cycles," Tinbergen Institute Discussion Papers 03-052/4, Tinbergen Institute.
- Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009.
"Real-Time Measurement of Business Conditions,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
- Chiara Scotti & S.Boragan Aruoba & Francis X. Diebold & University of Maryland, 2006. "Real-Time Measurement of Business Conditions," Computing in Economics and Finance 2006 387, Society for Computational Economics.
- S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2008. "Real-Time Measurement of Business Conditions," NBER Working Papers 14349, National Bureau of Economic Research, Inc.
- S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-Time Measurement of Business Conditions," PIER Working Paper Archive 07-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2008. "Real-time measurement of business conditions," Working Papers 08-19, Federal Reserve Bank of Philadelphia.
- S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-time measurement of business conditions," International Finance Discussion Papers 901, Board of Governors of the Federal Reserve System (U.S.).
- Tom Doan, "undated". "RATS programs to replicate Aruoba, Diebold and Scotti JBES 2009," Statistical Software Components RTZ00002, Boston College Department of Economics.
More about this item
Keywords
time series; recurrent neural networks; long short-term memory (LSTM); self-organising map (SOM); DeepAR; groundwater;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:9:p:5091-:d:799447. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.