3. Gatto N M, Henderson V W, Hodis H N, et al. Components of air pollution and cognitive function in middle-aged and older adults in Los Angeles. Neurotoxicology, 2014, 40(1): 1-7.
[4]
4. Vierk?tter A, Schikowski T, Ranft U, et al. Airborne particle exposure and extrinsic skin aging. J Invest Dermatol, 2010, 130(12): 2719-2726.
[5]
5. Cai Yuanyuan, Zhang Bo, Ke Weixia, et al. Associations of short-term and long-term exposure to ambient air pollutants with hypertension: a systematic review and meta-analysis. Hypertension, 2016, 68(1): 62-70.
[6]
6. Zanobetti A, Dominici F, Wang Yun, et al. A National case-crossover analysis of the short-term effect of PM2.5 on hospitalizations and mortality in subjects with diabetes and neurological disorders. Environ Health, 2014, 13(1): 38.
[7]
7. Adar S D, Sheppard L, Vedal S, et al. Fine particulate air pollution and the progression of carotid intima-medial thickness: a prospective cohort study from the multi-ethnic study of atherosclerosis and air pollution. PLoS Med, 2013, 10(4): e1001430.
[8]
8. Yanosky J D, Paciorek C J, Laden F, et al. Spatio-temporal modeling of particulate air pollution in the conterminous United States using geographic and meteorological predictors. Environ Health, 2014, 13: 63.
[9]
9. Mordukhovich I, Coull B, Kloog I, et al. Exposure to sub-chronic and long-term particulate air pollution and heart rate variability in an elderly cohort: the Normative Aging Study. Environ Health, 2015, 14(1): 87.
12. Bao Xinzhong, Tao Qiuyan, Fu Hongyu. Dynamic financial distress prediction based on Kalman filtering. J Appl Stat, 2015, 42(2): 292-308.
[13]
13. Xie Yinghong, Han Xiaowei, Li Qi. Research on applied-information technology with PM2.5 generation and evolution model based on BP neural network. Adv Mater Res, 2014, 3401(1003): 226-229.
[14]
14. Lozhkina O, Lozhkin V, Nevmerzhitsky N, et al. Motor transport related harmful PM2.5 and PM10: from onroad measurements to the modelling of air pollution by neural network approach on street and urban level. J Phys Conf Ser, 2016, 772(1): 12-15.
[15]
15. Hou Weizhen, Li Zhengqiang, Zhang Yuhuan, et al. Using support vector regression to predict PM10 and PM2.5. IOP Conference Series: Earth and Environmental Science, 2014, 17(1): 12268-12273.