Incremental fast relevance vector regression model based multi-pollutant emission prediction of biomass cogeneration systems

Exact and trusty prediction of pollutant emissions is pivotal for optimal combustion control in biomass cogeneration systems, which possess multiple variables, high-volume data streams, and dynamic characteristics. Aiming at the multivariate dynamic systems, this paper extends a classical fast relev...

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Vydané v:	Control engineering practice Ročník 149; s. 105986
Hlavní autori:	Wang, Xiuli, Sun, Zhifei, He, Defeng, Wu, Shaomin, Zhao, Lianna
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.08.2024
Predmet:	Extended fast relevance vector regression algorithm Incremental learning method k-means clustering method Pollutant emission prediction Extended fast relevance vector regression algorithm Pollutant emission prediction Incremental learning method k-means clustering method
ISSN:	0967-0661, 1873-6939
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