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Multiple time series forecasting using quasi-randomized functional link neural networks

Moudiki, Thierry; Planchet, Frédéric; Cousin, Areski - In: Risks : open access journal 6 (2018) 1, pp. 1-20

We are interested in obtaining forecasts for multiple time series, by taking into account the potential nonlinear relationships between their observations. For this purpose, we use a specific type of regression model on an augmented dataset of lagged time series. Our model is inspired by dynamic...

Persistent link: https://www.econbiz.de/10011811615

Machine learning advances for time series forecasting

Masini, Ricardo P.; Medeiros, Marcelo C.; Mendes, Eduardo F. - 2020

series forecasting. We consider both linear and nonlinear alternatives. Among the linear methods we pay special attention to …

Persistent link: https://www.econbiz.de/10012390030

Modelling tourism demand to Spain with machine learning techniques : the impact of forecast horizon on model selection

Claveria, Oscar; Torra, Salvador; Monte, Enric - In: Revista de economía aplicada : REA 24 (2016) 72, pp. 109-132

Persistent link: https://www.econbiz.de/10012261644

Machine learning advances for time series forecasting

Masini, Ricardo P.; Medeiros, Marcelo C.; Mendes, Eduardo F. - In: Journal of economic surveys 37 (2023) 1, pp. 76-111

Persistent link: https://www.econbiz.de/10014287800

Forecasting value-at-risk using deep neural network quantile regression

Chronopoulos, Ilias; Raftapostolos, Aristeidis; … - In: Journal of financial econometrics 22 (2024) 3, pp. 636-669

Persistent link: https://www.econbiz.de/10015045167

An intelligent algorithm for optimum forecasting of manufacturing lead times in fuzzy and crisp environments

Azadeh, Mohammad Ali; Ziaeifar, Amin; Pichka, Khosro; … - In: International journal of logistics systems and management 16 (2013) 2, pp. 186-210

Persistent link: https://www.econbiz.de/10010222775

Modeling and forecasting US presidential election using learning algorithms

Zolghadr, Mohammad; Niaki, Seyed Armin Akhavan; Niaki, … - In: Journal of industrial engineering international 14 (2018) 3, pp. 491-500

The primary objective of this research is to obtain an accurate forecasting model for the US presidential election. To …

Persistent link: https://www.econbiz.de/10011887885

Artificial neural network regression models : predicting GDP growth

Jahn, Malte - 2018

forecasting, as demonstrated by out-of-sample predictions for 2017. …

Persistent link: https://www.econbiz.de/10011897260

A unique support vector regression for improved modelling and forecasting of short-term gasoline consumption in railway systems

Azadeh, Mohammad Ali; Boskabadi, Azam; Pashapour, Shima - In: International journal of services and operations management 21 (2015) 2, pp. 217-237

Persistent link: https://www.econbiz.de/10011380081

Intelligent forecasting of economic growth for developing economies

Chuku, Chuku Agbai; Simpasa, Anthony Musonda; Oduor, Jacob - In: International economics : a journal published by CEPII … 159 (2019), pp. 74-93

Persistent link: https://www.econbiz.de/10012318821