Comparison of ARIMA, neural networks and hybrid models in time series: tourist arrival forecasting

DOI10.1080/10629360600564874zbMath1109.62081OpenAlexW2100115021MaRDI QIDQ3432728

Senay Yolacan, Berna Yazici, Atilla Aslanargun, Mammadagha Mammadov

Publication date: 18 April 2007

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10629360600564874

zbMATH Keywords

neural networkstime seriesbackpropagationARIMAradial basis function networkhybrid models

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Statistical tables (62Q05) Neural nets and related approaches to inference from stochastic processes (62M45)

Related Items (3)

Weighted sequential hybrid approaches for time series forecasting ⋮ A sliding window-based multi-stage clustering and probabilistic forecasting approach for large multivariate time series data ⋮ How to control the crack to propagate along the specified path feasibly?

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