Daily PM 2.5 concentration prediction based on principal component analysis and LSSVM optimized by cuckoo search algorithm-Reference-Cited by-同舟云学术

Daily PM 2.5 concentration prediction based on principal component analysis and LSSVM optimized by cuckoo search algorithm

Published:2017-03 Issue: Volume:188 Page:144-152
ISSN:0301-4797
Container-title:Journal of Environmental Management
language:en
Short-container-title:Journal of Environmental Management

Author:

Sun Wei,Sun Jingyi

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Waste Management and Disposal,General Medicine,Environmental Engineering

Reference36 articles.

1. A neural network based on ensemble approach for improving the accuracy of meteorological fields used for regional air quality modeling;Cheng;J. Environ. Manag.,2014

2. Traffic flow forecasting by a least squares support vector machine with a fruit fly optimization algorithm;Cong;Proced. Eng.,2016

3. A hybrid ARIMA and artificial neural networks model to forecast particulate matter in urban areas: the case of Temuco, Chile;Díaz-Robles;Atmos. Environ.,2008

4. Real time air quality forecasting using integrated parametric and non-parametric regression techniques;Donnelly;Atmos. Environ.,2015

5. Artificial neural networks forecasting of PM2.5 pollution using air mass trajectory based geographic model and wavelet transformation;Feng;Atmos. Environ.,2015

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