The two-stage machine learning ensemble models for stock price prediction by combining mode decomposition, extreme learning machine and improved harmony search algorithm

DOI10.1007/s10479-020-03690-wOpenAlexW3036522266MaRDI QIDQ2070766

Wei Chen, Manrui Jiang, Lifen Jia, Zhensong Chen

Publication date: 24 January 2022

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-020-03690-w

zbMATH Keywords

empirical mode decompositionensemble learningharmony searchstock price predictionvariational mode decomposition

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from stochastic processes and prediction (62M20) Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (3)

Forecasting carbon futures price: a hybrid method incorporating fuzzy entropy and extreme learning machine ⋮ Data-driven decision model based on local two-stage weighted ensemble learning ⋮ Multi-period portfolio selection based on uncertainty theory with bankruptcy control and liquidity

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