Weighted sequential hybrid approaches for time series forecasting

DOI10.1016/j.physa.2019.121717OpenAlexW2952740974MaRDI QIDQ2162543

Zahra Hajirahimi, Mehdi Khashei

Publication date: 8 August 2022

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physa.2019.121717

zbMATH Keywords

time series forecastingleast squares techniquemultilayer perceptrons (MLPs)autoregressive integrated moving average (ARIMA)sequential hybrid modelsweighted sequential methodology

Mathematics Subject Classification ID

Statistical mechanics, structure of matter (82-XX)

Related Items (1)

Series hybridization of parallel (SHOP) models for time series forecasting

Cites Work

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• Time series forecasting using a hybrid ARIMA and neural network model
• Handbook of economic forecasting. Volume 1
• A new solution to one sample problem in face recognition using FLDA
• Forecasting nonlinear time series with a hybrid methodology
• Chaotic oscillations and cycles in multi-trophic ecological systems
• Comparison of ARIMA, neural networks and hybrid models in time series: tourist arrival forecasting

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