Analytics Saves Lives During the COVID-19 Crisis in Chile
Author
Abstract
Suggested Citation
DOI: 10.1287/inte.2022.1149
Download full text from publisher
References listed on IDEAS
- Marcel Goic & Mirko S Bozanic-Leal & Magdalena Badal & Leonardo J Basso, 2021. "COVID-19: Short-term forecast of ICU beds in times of crisis," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-24, January.
- Zhang, G. Peter & Qi, Min, 2005. "Neural network forecasting for seasonal and trend time series," European Journal of Operational Research, Elsevier, vol. 160(2), pages 501-514, January.
- Montgomery, Jacob M. & Hollenbach, Florian M. & Ward, Michael D., 2015. "Calibrating ensemble forecasting models with sparse data in the social sciences," International Journal of Forecasting, Elsevier, vol. 31(3), pages 930-942.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Gustavo Quinderé Saraiva, 2023. "Pool testing with dilution effects and heterogeneous priors," Health Care Management Science, Springer, vol. 26(4), pages 651-672, December.
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.- Yuxin Zhang & Yifei Yang & Xiaosi Li & Zijing Yuan & Yuki Todo & Haichuan Yang, 2023. "A Dendritic Neuron Model Optimized by Meta-Heuristics with a Power-Law-Distributed Population Interaction Network for Financial Time-Series Forecasting," Mathematics, MDPI, vol. 11(5), pages 1-20, March.
- Aldo Carranza & Marcel Goic & Eduardo Lara & Marcelo Olivares & Gabriel Y. Weintraub & Julio Covarrubia & Cristian Escobedo & Natalia Jara & Leonardo J. Basso, 2022. "The Social Divide of Social Distancing: Shelter-in-Place Behavior in Santiago During the Covid-19 Pandemic," Management Science, INFORMS, vol. 68(3), pages 2016-2027, March.
- Hewamalage, Hansika & Bergmeir, Christoph & Bandara, Kasun, 2021. "Recurrent Neural Networks for Time Series Forecasting: Current status and future directions," International Journal of Forecasting, Elsevier, vol. 37(1), pages 388-427.
- Marcjasz, Grzegorz & Uniejewski, Bartosz & Weron, Rafał, 2019. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1520-1532.
- Curry, Bruce, 2007. "Neural networks and seasonality: Some technical considerations," European Journal of Operational Research, Elsevier, vol. 179(1), pages 267-274, May.
- Nataša Glišović & Miloš Milenković & Nebojša Bojović & Libor Švadlenka & Zoran Avramović, 2016. "A hybrid model for forecasting the volume of passenger flows on Serbian railways," Operational Research, Springer, vol. 16(2), pages 271-285, July.
- Crone, Sven F. & Hibon, Michèle & Nikolopoulos, Konstantinos, 2011.
"Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction,"
International Journal of Forecasting, Elsevier, vol. 27(3), pages 635-660.
- Crone, Sven F. & Hibon, Michèle & Nikolopoulos, Konstantinos, 2011. "Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction," International Journal of Forecasting, Elsevier, vol. 27(3), pages 635-660, July.
- Zhang, Rong & Ashuri, Baabak & Shyr, Yu & Deng, Yong, 2018. "Forecasting Construction Cost Index based on visibility graph: A network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 239-252.
- Lalou Panagiota & Ponis Stavros T. & Efthymiou Orestis K., 2020. "Demand Forecasting of Retail Sales Using Data Analytics and Statistical Programming," Management & Marketing, Sciendo, vol. 15(2), pages 186-202, June.
- Long Wen & Chang Liu & Haiyan Song, 2019. "Forecasting tourism demand using search query data: A hybrid modelling approach," Tourism Economics, , vol. 25(3), pages 309-329, May.
- Icaro Romolo Sousa Agostino & Wesley Vieira da Silva & Claudimar Pereira da Veiga & Adriano Mendonça Souza, 2020. "Forecasting models in the manufacturing processes and operations management: Systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1043-1056, November.
- Soolmaz L. Azarmi & Akeem Adeyemi Oladipo & Roozbeh Vaziri & Habib Alipour, 2018. "Comparative Modelling and Artificial Neural Network Inspired Prediction of Waste Generation Rates of Hospitality Industry: The Case of North Cyprus," Sustainability, MDPI, vol. 10(9), pages 1-18, August.
- Voyant, Cyril & Muselli, Marc & Paoli, Christophe & Nivet, Marie-Laure, 2011. "Optimization of an artificial neural network dedicated to the multivariate forecasting of daily global radiation," Energy, Elsevier, vol. 36(1), pages 348-359.
- Ben Moews & J. Michael Herrmann & Gbenga Ibikunle, 2018. "Lagged correlation-based deep learning for directional trend change prediction in financial time series," Papers 1811.11287, arXiv.org, revised Nov 2018.
- Jônatas Belotti & Hugo Siqueira & Lilian Araujo & Sérgio L. Stevan & Paulo S.G. de Mattos Neto & Manoel H. N. Marinho & João Fausto L. de Oliveira & Fábio Usberti & Marcos de Almeida Leone Filho & Att, 2020. "Neural-Based Ensembles and Unorganized Machines to Predict Streamflow Series from Hydroelectric Plants," Energies, MDPI, vol. 13(18), pages 1-22, September.
- Tschora, Léonard & Pierre, Erwan & Plantevit, Marc & Robardet, Céline, 2022. "Electricity price forecasting on the day-ahead market using machine learning," Applied Energy, Elsevier, vol. 313(C).
- Salcedo-Sanz, Sancho & Ángel M. Pérez-Bellido, & Ortiz-García, Emilio G. & Portilla-Figueras, Antonio & Prieto, Luis & Paredes, Daniel, 2009. "Hybridizing the fifth generation mesoscale model with artificial neural networks for short-term wind speed prediction," Renewable Energy, Elsevier, vol. 34(6), pages 1451-1457.
- Wong, W.K. & Guo, Z.X., 2010. "A hybrid intelligent model for medium-term sales forecasting in fashion retail supply chains using extreme learning machine and harmony search algorithm," International Journal of Production Economics, Elsevier, vol. 128(2), pages 614-624, December.
- Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2023.
"A Hybrid ARFIMA Wavelet Artificial Neural Network Model for DJIA Index Forecasting,"
Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1801-1843, December.
- Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2020. "Hybrid ARFIMA Wavelet Artificial Neural Network Model for DJIA Index Forecasting," Working Papers 202056, University of Pretoria, Department of Economics.
- Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2020. "Hybrid ARFIMA Wavelet Artificial Neural Network Model for DJIA Index Forecasting," Working papers 2020-10, University of Connecticut, Department of Economics.
- Dr. Murat çuhadar & Iclal Cogurcu & Ceyda Kukrer, 2014. "Modelling and Forecasting Cruise Tourism Demand to Izmir by Different Artificial Neural Network Architectures," International Journal of Business and Social Research, LAR Center Press, vol. 4(3), pages 12-28, March.
More about this item
Keywords
COVID-19 pandemic; data science; data-driven decision making; public policy; Edelman award;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:inm:orinte:v:53:y:2023:i:1:p:9-31. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.