Improved pollution forecasting hybrid algorithms based on the ensemble method

DOI10.1016/j.apm.2019.04.032zbMath1481.86026OpenAlexW2939347301MaRDI QIDQ1984969

Hui Liu, Chao Chen, Yinan Xu

Publication date: 7 April 2020

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

Full work available at URL: https://doi.org/10.1016/j.apm.2019.04.032

zbMATH Keywords

hybrid forecasting modelstacking ensemble methodurban fine particle concentration forecasting

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12) Geostatistics (86A32)

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The two-stage machine learning ensemble models for stock price prediction by combining mode decomposition, extreme learning machine and improved harmony search algorithm ⋮ Novel hybrid extreme learning machine and multi-objective optimization algorithm for air pollution prediction

Cites Work

• Relaxed support vector regression
• Alternating Direction Algorithms for $\ell_1$-Problems in Compressive Sensing
• Variational Mode Decomposition

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