AGRIS — международная информационная система по сельскохозяйственным наукам и технологиям

A novel hybrid-Garch model based on Arima and SVM for PM2.5 concentrations forecasting

2017

Wang, Ping | Zhang, Hong | Qin, Zuodong | Zhang, Guisheng


Библиографическая информация
Atmospheric Pollution Research
ISSN 1309-1042
Издатель
Elsevier B.V.
Другие темы
Generalized autoregressive conditional heteroskedasticity (garch); Air pollution forecasting; Variance; Hybrid-garch forecasting model; Nonlinear models; Support vector machines; Support vector machine (svm); Emissions; Heteroskedasticity; Autoregressive integrated moving average (arima); Work schedules
Язык
Английский
Примечание
Pre-press version
Тип
Journal Article; Text

2024-02-27
MODS
Посмотрите в Google Scholar
If you notice any incorrect information relating to this record, please contact us at agris@fao.org agris@fao.org