A novel hybrid decomposition-ensemble model based on VMD and HGWO for container throughput forecasting

DOI10.1016/j.apm.2018.01.014zbMath1480.90063OpenAlexW2791961911MaRDI QIDQ2295254

Yueyong Hu, Shaolong Sun, Yu Liu, Mingfei Niu

Publication date: 12 February 2020

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2018.01.014

zbMATH Keywords

support vector regressioncontainer throughput forecastingvariational mode decompositionhybrid decomposition-ensemble modelhybridizing grey wolf optimization

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Applications of mathematical programming (90C90) Transportation, logistics and supply chain management (90B06)

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Uses Software

• GWO

Cites Work

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• Time series forecasting using a hybrid ARIMA and neural network model
• Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
• Forecasting exchange rates using general regression neural networks
• A hybrid forecasting approach applied in the electrical power system based on data preprocessing, optimization and artificial intelligence algorithms
• Forecasting container throughput of Qingdao Port with a hybrid model
• Variational Mode Decomposition

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