With the rapid growth in the availability of data and computational technologies, multiple
machine learning frameworks have been proposed for forecasting air pollution. However …

Timely and accurate air quality forecasting is of great significance for prevention and
mitigation of air pollution. However, most of the previous forecasting models only considered …

With rising levels of air-pollution, air-quality forecasting has become integral to the
dissemination of human health advisories and the preparation of mitigation strategies. To …

In fuzzy information granule (FIG) based short-term forecasting models, the constructed FIG
focuses on one of two tasks: capture data characteristic and improve semantic description at …

This study deals with the simulation and prediction of air pollutants in Irbid city (north of
Jordan) before and during the spread of the COVID-19 virus pandemic by using an artificial …

中国空气污染问题日益严重, 为获得连续的PM2. 5 浓度空间分布, 现有研究建立了多种基于统计
回归的PM2. 5 估算模型. 然而, 由于PM2. 5 回归关系显著的空间非平稳性和复杂的非线性特征 …

A prognosis model has been developed for solid waste generation from households in Hoi
An City, a famous tourist city in Viet Nam. Waste sampling, followed by a questionnaire …

Air pollution became fatal issue for humanity and all environment and developed countries
unanimously allocated vast investments on monitoring and researches about air pollutants …

Forecasting PM2. 5 concentration in ambient air quality is of great concern to urban
management administrative due to its harmful health consequences and interference with …

The risk of a broad range of respiratory and heart diseases can be increased by widespread
exposure to fine atmospheric particles on account of their capability to have a deep …