E3S Web Conf.
Volume 194, 20202020 5th International Conference on Advances in Energy and Environment Research (ICAEER 2020)
|Number of page(s)||5|
|Section||Environmental Engineering, Ecological Environment and Urban Construction|
|Published online||15 October 2020|
Study on the Influence of Air Pressure and Temperature on PM2.5 by Multivariate Functional Linear Regression Model
College of Science, North China University of Technology, P.R. China
* Corresponding author: firstname.lastname@example.org
In recent years, the Internet has developed rapidly, and we have more and more ways to collect data. We find that many data have the characteristics of functions. We can use the important method of functional data analysis to analyze these data. The basic idea of functional data analysis is to treat data with functional properties as a whole for analysis and corresponding processing. In this paper, the daily air pressure, temperature and PM2.5 data of 49 cities with serious PM2.5 pollution in 2017 are sorted out. We use a multivariate functional linear regression model to discuss the influence of pressure and temperature on PM2.5 when the number of basis functions is different.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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