Spatio-temporal forecasting using wavelet transform-based decision trees with application to air quality and covid-19 forecasting-Reference-Cited by-同舟云学术

Spatio-temporal forecasting using wavelet transform-based decision trees with application to air quality and covid-19 forecasting

Published:2022-04-25 Issue: Volume: Page:1-19
ISSN:0266-4763
Container-title:Journal of Applied Statistics
language:en
Short-container-title:Journal of Applied Statistics

Author:

Zhao Xin¹²,Barber Stuart²^ORCID,Taylor Charles C²,Nie Xiaokai³,Shen Wenqian¹

Affiliation:

1. School of Mathematics, Southeast University, Nanjing, People's Republic of China

2. School of Mathematics, University of Leeds, Leeds, UK

3. School of Automation, Southeast University, Nanjing, People's Republic of China

Funder

the Fundamental Research Funds for the Central Universities

Guangdong Basic and Applied Basic Research Foundation

Natural Science Foundation of Jiangsu Province

Nanjing Scientific and Technological Innovation Foundation for Selected Returned Overseas Chinese Scholars

Jiangsu Foundation for Innovative and Entrepreneurial Doctor

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/02664763.2022.2064976

Reference44 articles.

1. AirNow, Aqi basics, preprint (2020). Available at https://www.airnow.gov/aqi/aqi-basics/. [cited 2020 Jun 03].

2. AirVisual I, 2018 world air quality report, preprint (2018). Available at https://www.airvisual.com/world-most-polluted-cities/world-air-quality-report-2018-en.pdf [cited 2020 Apr 03].

3. Classification of multiple time signals using localized frequency characteristics applied to industrial process monitoring

4. The relationship between industrial restructuring and China's regional haze pollution: A spatial spillover perspective

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