Prediction of $$\hbox {PM}_{2.5}$$ concentration based on weighted bagging and image contrast-sensitive features-Reference-Cited by-同舟云学术

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Prediction of $$\hbox {PM}_{2.5}$$ concentration based on weighted bagging and image contrast-sensitive features

Published:2020-03-10 Issue:3-4 Volume:34 Page:561-573
ISSN:1436-3240
Container-title:Stochastic Environmental Research and Risk Assessment
language:en
Short-container-title:Stoch Environ Res Risk Assess

Author:

Qiao Junfei,He Zengzeng,Du Shengli

Funder

National Natural Science Foundation of China

National Major Science and Technology Projects of China

National Basic Research Program of China (973 Program)

Publisher

Springer Science and Business Media LLC

Subject

General Environmental Science,Safety, Risk, Reliability and Quality,Water Science and Technology,Environmental Chemistry,Environmental Engineering

Link

http://link.springer.com/content/pdf/10.1007/s00477-020-01787-z.pdf

Reference49 articles.

1. Anderson TL, Ogren JA (1998) Determining aerosol radiative properties using the TSI 3563 integrating nephelometer. Aerosol Sci Technol 29(1):57–69. https://doi.org/10.1080/02786829808965551

2. Azid A, Juahir H, Toriman ME, Kamarudin MKA, Saudi ASM, Hasnam CNC, Aziz NAA, Azaman F, Latif MT, Zainuddin SFM et al (2014) Prediction of the level of air pollution using principal component analysis and artificial neural network techniques: a case study in Malaysia. Water Air Soil Pollut 225(8):2063. https://doi.org/10.1007/s11270-014-2063-1

3. Bologna G, Yvon C, Duvaud S, Veuthey AL (2004) N-terminal myristoylation predictions by ensembles of neural networks. Proteomics 4(6):1626–1632. https://doi.org/10.1002/pmic.200300783

4. Breiman L (1996) Bagging predictors. Mach Learn 24(2):123–140. https://doi.org/10.1007/BF00058655

5. Broomhead DS, Lowe D (1988) Radial basis functions, multi-variable functional interpolation and adaptive networks. Tech. Rep. RSRE-MEMO-4148

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