Regional Forecasting of Fine Particulate Matter Concentrations: A Novel Hybrid Model Based on Principal Component Regression and EOF-Reference-Cited by-同舟云学术

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Regional Forecasting of Fine Particulate Matter Concentrations: A Novel Hybrid Model Based on Principal Component Regression and EOF

Published:2021-07 Issue:7 Volume:8 Page:
ISSN:2333-5084
Container-title:Earth and Space Science
language:en
Short-container-title:Earth Space Sci

Author:

Wu Xianghua¹²^ORCID,Xie Kang¹,Liu Jane²^ORCID,Liu Duanyang³,Zhou Jieqin¹,Tang Lili⁴^ORCID

Affiliation:

1. School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing China

2. Department of Geography and Planning University of Toronto Toronto ON Canada

3. Key Laboratory of Transportation Meteorology China Meteorological Administration Nanjing China

4. School of Environmental Science and Engineering Nanjing University of Information Science and Technology Nanjing China

Funder

Innovative Research Group Project of the National Natural Science Foundation of China

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Environmental Science (miscellaneous)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021EA001694

Reference63 articles.

1. Statistical downscaling of an air quality model using Fitted Empirical Orthogonal Functions

2. Forecast of PM10 time-series data: A study case in Caribbean cities

3. Neural Models for Imputation of Missing Ozone Data in Air-Quality Datasets

4. Assessing the accuracy of ANFIS, EEMD-GRNN, PCR, and MLR models in predicting PM2.5

5. Haze Days in North China and the associated atmospheric circulations based on daily visibility data from 1960 to 2012

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