Partially connected feedforward neural networks on Apollonian networks
Author
Abstract
Suggested Citation
DOI: 10.1016/j.physa.2010.06.061
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Li Huang & Jian Huang & Wei Wang, 2018. "The Sustainable Development Assessment of Reservoir Resettlement Based on a BP Neural Network," IJERPH, MDPI, vol. 15(1), pages 1-15, January.
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.- Hendry, David F. & Clements, Michael P., 2003.
"Economic forecasting: some lessons from recent research,"
Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
- David Hendry & Michael P. Clements, 2001. "Economic Forecasting: Some Lessons from Recent Research," Economics Papers 2002-W11, Economics Group, Nuffield College, University of Oxford.
- Clements, Michael P. & Hendry, David F., 2001. "Economic forecasting: some lessons from recent research," Working Paper Series 82, European Central Bank.
- Hendry, David F & Michael P. Clements, 2002. "Economic Forecasting: Some Lessons from Recent Research," Royal Economic Society Annual Conference 2002 99, Royal Economic Society.
- David Hendry & Michael P. Clements & Department of Economics & University of Warwick, 2001. "Economic Forecasting: Some Lessons from Recent Research," Economics Series Working Papers 78, University of Oxford, Department of Economics.
- Tsionas, Mike G., 2021. "Bayesian forecasting with the structural damped trend model," International Journal of Production Economics, Elsevier, vol. 234(C).
- Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
- Clements, Michael P. & Beatriz Galvao, Ana, 2010.
"Real-time Forecasting of Inflation and Output Growth in the Presence of Data Revisions,"
Economic Research Papers
270771, University of Warwick - Department of Economics.
- Clements, Michael P. & Galvão, Ana Beatriz, 2010. "Real-time Forecasting of Inflation and Output Growth in the Presence of Data Revisions," The Warwick Economics Research Paper Series (TWERPS) 953, University of Warwick, Department of Economics.
- Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015.
"Golden rule of forecasting: Be conservative,"
Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
- Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2014. "Golden Rule of Forecasting: Be conservative," MPRA Paper 53579, University Library of Munich, Germany.
- Hyndman, Rob J. & Ahmed, Roman A. & Athanasopoulos, George & Shang, Han Lin, 2011.
"Optimal combination forecasts for hierarchical time series,"
Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2579-2589, September.
- Rob J. Hyndman & Roman A. Ahmed & George Athanasopoulos, 2007. "Optimal combination forecasts for hierarchical time series," Monash Econometrics and Business Statistics Working Papers 9/07, Monash University, Department of Econometrics and Business Statistics.
- Kourentzes, Nikolaos & Petropoulos, Fotios & Trapero, Juan R., 2014. "Improving forecasting by estimating time series structural components across multiple frequencies," International Journal of Forecasting, Elsevier, vol. 30(2), pages 291-302.
- İhsan Erdem Kayral & Tuğba Sarı & Nisa Şansel Tandoğan Aktepe, 2023. "Forecasting the Tourist Arrival Volumes and Tourism Income with Combined ANN Architecture in the Post COVID-19 Period: The Case of Turkey," Sustainability, MDPI, vol. 15(22), pages 1-20, November.
- Alysha M De Livera, 2010. "Automatic forecasting with a modified exponential smoothing state space framework," Monash Econometrics and Business Statistics Working Papers 10/10, Monash University, Department of Econometrics and Business Statistics.
- Litsiou, Konstantia & Polychronakis, Yiannis & Karami, Azhdar & Nikolopoulos, Konstantinos, 2022. "Relative performance of judgmental methods for forecasting the success of megaprojects," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1185-1196.
- Miroslav Navratil & Andrea Kolkova, 2019. "Decomposition and Forecasting Time Series in the Business Economy Using Prophet Forecasting Model," Central European Business Review, Prague University of Economics and Business, vol. 2019(4), pages 26-39.
- Antonio Fernández-Cano & Manuel Torralbo & Mónica Vallejo, 2012. "Time series of scientific growth in Spanish doctoral theses (1848–2009)," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 15-36, April.
- Meira, Erick & Cyrino Oliveira, Fernando Luiz & de Menezes, Lilian M., 2022. "Forecasting natural gas consumption using Bagging and modified regularization techniques," Energy Economics, Elsevier, vol. 106(C).
- Klinger, Sabine & Heilemann, Ullrich, 2005. "Zu wenig Wettbewerb? Zu Stand und Entwicklung der Genauigkeit makroökonomischer Prognosen," Technical Reports 2005,16, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Spiliotis, Evangelos & Petropoulos, Fotios, 2024. "On the update frequency of univariate forecasting models," European Journal of Operational Research, Elsevier, vol. 314(1), pages 111-121.
- Fantazzini, Dean, 2020.
"Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries,"
Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 33-54.
- Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," MPRA Paper 102315, University Library of Munich, Germany.
- Kock, Anders Bredahl & Teräsvirta, Timo, 2014.
"Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009,"
International Journal of Forecasting, Elsevier, vol. 30(3), pages 616-631.
- Anders Bredahl Kock & Timo Teräsvirta, 2011. "Forecasting performance of three automated modelling techniques during the economic crisis 2007-2009," CREATES Research Papers 2011-28, Department of Economics and Business Economics, Aarhus University.
- N. N. Taleb & R. Douady, 2013.
"Mathematical definition, mapping, and detection of (anti)fragility,"
Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1677-1689, November.
- Nassim N. Taleb & Raphael Douady, 2012. "Mathematical Definition, Mapping, and Detection of (Anti)Fragility," Papers 1208.1189, arXiv.org.
- Nassim Nicholas Taleb & Raphaël Douady, 2014. "Mathematical Definition, Mapping, and Detection of (Anti)Fragility," Post-Print hal-01151340, HAL.
- Nassim Nicholas Taleb & Raphaël Douady, 2014. "Mathematical Definition, Mapping, and Detection of (Anti)Fragility," Documents de travail du Centre d'Economie de la Sorbonne 14093, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
- N. N. Taleb & Raphaël Douady, 2013. "Mathematical Definition, Mapping, and Detection of (Anti)fragility," Post-Print hal-01052645, HAL.
- Nassim Nicholas Taleb & Raphaël Douady, 2014. "Mathematical Definition, Mapping, and Detection of (Anti)Fragility," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01151340, HAL.
- N. N. Taleb & Raphaël Douady, 2013. "Mathematical Definition, Mapping, and Detection of (Anti)fragility," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01052645, HAL.
- Thiyanga S Talagala & Rob J Hyndman & George Athanasopoulos, 2018. "Meta-learning how to forecast time series," Monash Econometrics and Business Statistics Working Papers 6/18, Monash University, Department of Econometrics and Business Statistics.
- Claudio M. Rocco & Kash Barker & Jose Moronta, 2022. "Determining the best algorithm to detect community structures in networks: application to power systems," Environment Systems and Decisions, Springer, vol. 42(2), pages 251-264, June.
More about this item
Keywords
Feedforward neural networks; Partially connected neural networks; Apollonian networks; Randomly connected neural networks;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:eee:phsmap:v:389:y:2010:i:22:p:5298-5307. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.