Trend-attribute forecasting of hourly PM2.5 trends in fifteen cities of Central England applying optimized machine learning feature selection-Reference-Cited by-同舟云学术

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Trend-attribute forecasting of hourly PM2.5 trends in fifteen cities of Central England applying optimized machine learning feature selection

Published:2024-04 Issue: Volume:356 Page:120561
ISSN:0301-4797
Container-title:Journal of Environmental Management
language:en
Short-container-title:Journal of Environmental Management

Author:

Wood David A.^ORCID

Publisher

Elsevier BV

Reference73 articles.

1. Advances in sine cosine algorithm: a comprehensive survey;Abualigah;Artif. Intell. Rev.,2021

2. Measurement Uncertainty for PM2.5 in the Context of the UK National Network;Allan,2022

3. National Birth Defects Prevention Study. Associations between PM2.5 and risk of preterm birth among liveborn infants;Alman;Ann. Epidemiol.,2019

4. Dust storms modeling and their impacts on air quality and radiation budget over Iran using WRF-Chem;Ashrafi;Air Qual Atmos Health,2017

5. An ensemble long short-term memory neural network for hourly PM2.5 concentration forecasting;Bai;Chemosphere,2019

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel machine learning-based artificial intelligence method for predicting the air pollution index PM2.5;Journal of Cleaner Production;2024-08

2. The environmental consequences of national Audit governance: An analysis based on county-level data in China;Journal of Environmental Management;2024-05

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