A novel hybrid model for air quality index forecasting based on two-phase decomposition technique and modified extreme learning machine.

Wang, Deyun; Wei, Shuai; Luo, Hongyuan; Yue, Chenqiang; Grunder, Olivier

Wang, Deyun; Wei, Shuai; Luo, Hongyuan; Yue, Chenqiang; Grunder, Olivier.

Affiliation

Wang D; School of Economics and Management, China University of Geosciences, Wuhan 430074, China; Mineral Resource Strategy and Policy Research Center, China University of Geosciences, Wuhan 430074, China; Université de Bourgogne Franche-Comté, UTBM, IRTES, Rue Thierry Mieg, 90010 Belfort cedex, France. Ele
Wei S; School of Economics and Management, China University of Geosciences, Wuhan 430074, China; Mineral Resource Strategy and Policy Research Center, China University of Geosciences, Wuhan 430074, China.
Luo H; School of Economics and Management, China University of Geosciences, Wuhan 430074, China; Mineral Resource Strategy and Policy Research Center, China University of Geosciences, Wuhan 430074, China.
Yue C; School of Economics and Management, China University of Geosciences, Wuhan 430074, China; Mineral Resource Strategy and Policy Research Center, China University of Geosciences, Wuhan 430074, China.
Grunder O; Université de Bourgogne Franche-Comté, UTBM, IRTES, Rue Thierry Mieg, 90010 Belfort cedex, France.

Sci Total Environ ; 580: 719-733, 2017 Feb 15.

Article in En | MEDLINE | ID: mdl-27989476

Key words

Air quality index (AQI); Complementary ensemble empirical mode decomposition (CEEMD); Differential evolution (DE); Extreme learning machine (ELM); Variational mode decomposition (VMD)

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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Total Environ Year: 2017 Document type: Article Country of publication: Netherlands

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