Performance analysis of four decomposition-ensemble models for one-day-ahead agricultural commodity futures price forecasting

DOI10.3390/a10030108zbMath1461.91209OpenAlexW2755418557MaRDI QIDQ1657097

Shuai Wei, Jun Lv, Deyun Wang, Chenqiang Yue

Publication date: 13 August 2018

Published in: Algorithms (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3390/a10030108

zbMATH Keywords

decomposition methodsparticle swarm optimization (PSO)back propagation neural network (BPNN)agricultural commodity futures prices

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Economic time series analysis (91B84) Applications of mathematical programming (90C90) Approximation methods and heuristics in mathematical programming (90C59)

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An equilibrium analysis of the impact of real estate price volatility on macroeconomics based on ant colony algorithm ⋮ The analysis of commodity demand predication in supply chain network based on particle swarm optimization algorithm

Cites Work

• A hybrid forecasting approach applied in the electrical power system based on data preprocessing, optimization and artificial intelligence algorithms
• A theory for multiresolution signal decomposition: the wavelet representation
• The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
• Variational Mode Decomposition
• Intrinsic time-scale decomposition: time–frequency–energy analysis and real-time filtering of non-stationary signals

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