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
- 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).
- 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, December.
- 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.
- 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.
- 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.
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.- 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.
- 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.
- Victor Bystrov, 2018.
"Measuring the Natural Rates of Interest in Germany and Italy,"
Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(4), pages 333-353, December.
- Bystrov Victor, 2018. "Measuring the Natural Rates of Interest in Germany and Italy," Lodz Economics Working Papers 7/2018, University of Lodz, Faculty of Economics and Sociology.
- Yukai Yang & Luc Bauwens, 2018.
"State-Space Models on the Stiefel Manifold with a New Approach to Nonlinear Filtering,"
Econometrics, MDPI, vol. 6(4), pages 1-22, December.
- Yukai Yang & Luc Bauwens, 2018. "State-Space Models on the Stiefel Manifold with A New Approach to Nonlinear Filtering," CREATES Research Papers 2018-30, Department of Economics and Business Economics, Aarhus University.
- Yukai Yang & Luc Bauwens, 2018. "State-space models on the Stiefel Manifold with a new approach to nonlinear filtering," LIDAM Reprints CORE 2985, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Fernández-Macho, Javier, 2008. "Spectral estimation of a structural thin-plate smoothing model," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 189-195, September.
- Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
- 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.
- Chen, Peimin & Wu, Chunchi, 2014. "Default prediction with dynamic sectoral and macroeconomic frailties," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 211-226.
- repec:zbw:bofitp:2019_008 is not listed on IDEAS
- Yue Zhao & Difang Wan, 2018. "Institutional high frequency trading and price discovery: Evidence from an emerging commodity futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(2), pages 243-270, February.
- Wen Xu, 2016. "Estimation of Dynamic Panel Data Models with Stochastic Volatility Using Particle Filters," Econometrics, MDPI, vol. 4(4), pages 1-13, October.
- Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
- repec:spo:wpmain:info:hdl:2441/1904 is not listed on IDEAS
- Hári, Norbert & De Waegenaere, Anja & Melenberg, Bertrand & Nijman, Theo E., 2008. "Estimating the term structure of mortality," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 492-504, April.
- Brave, Scott A. & Gascon, Charles & Kluender, William & Walstrum, Thomas, 2021.
"Predicting benchmarked US state employment data in real time,"
International Journal of Forecasting, Elsevier, vol. 37(3), pages 1261-1275.
- Scott Brave & Charles S. Gascon & William Kluender & Thomas Walstrum, 2019. "Predicting Benchmarked US State Employment Data in Realtime," Working Paper Series WP 2019-11, Federal Reserve Bank of Chicago.
- Scott A. Brave & Charles S. Gascon & William Kluender & Thomas Walstrum, 2019. "Predicting Benchmarked US State Employment Data in Real Time," Working Papers 2019-037, Federal Reserve Bank of St. Louis, revised 11 Mar 2021.
- 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.
- Bógalo, Juan & Poncela, Pilar & Senra, Eva, 2017. "Automatic Signal Extraction for Stationary and Non-Stationary Time Series by Circulant SSA," MPRA Paper 76023, University Library of Munich, Germany.
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.