Forecasting air pollution particulate matter (PM2. 5) using machine learning regression models
… it is worth saying that modern approaches that combine machine learning methods with the
utilize of air pollution information to get it … model for predicting NO2 concentrations from traffic …
utilize of air pollution information to get it … model for predicting NO2 concentrations from traffic …
[HTML][HTML] Real-time in-vehicle air quality monitoring system using machine learning prediction algorithm
… It consists of five sensors that measure the level of CO 2 , … An IoT-oriented transportation
system is applied in this system by … A linear regression model is capable of time series …
system is applied in this system by … A linear regression model is capable of time series …
Time series data prediction using IoT and machine learning technique
… of IOT generated sensor’s data of various locations of National Capital Region (NCR).Sensor’s
data predict air quality of next day using linear regression model… factors like traffic density, …
data predict air quality of next day using linear regression model… factors like traffic density, …
[PDF][PDF] A Pre-to Post-COVID-19 Change of Air Quality Patterns in Anhui Province Using Path Analysis and Regression.
… and traffic. A similar pattern was observed for some of the … In this study, path analysis and
regression analysis were the main … same time, it analyzed the air quality regression of cities in …
regression analysis were the main … same time, it analyzed the air quality regression of cities in …
Quantifying road traffic impact on air quality in urban areas: A Covid19-induced lockdown analysis in Italy
… from the Copernicus Atmosphere Monitoring Service (CAMS, 2020) have been used. Reliability
of CAMS satellite irradiation was assessed by applying a linear regression against solar …
of CAMS satellite irradiation was assessed by applying a linear regression against solar …
Data analysis and mining of the correlations between meteorological conditions and air quality: A case study in Beijing
… the data mining method, random forests, to model the regression relationships between …
and traffic flow. Sun et al [12] analyzed the dynamic accumulation of PM2.5 using hourly …
and traffic flow. Sun et al [12] analyzed the dynamic accumulation of PM2.5 using hourly …
[HTML][HTML] Air quality prediction in smart cities using machine learning technologies based on sensor data: a review
… it had a tendency to increase, and (7) for efficient air quality … of life, such as transportation,
health care, air quality, etc. The smart … publications, the regression method was mainly applied …
health care, air quality, etc. The smart … publications, the regression method was mainly applied …
IoT enabled environmental toxicology for air pollution monitoring using AI techniques
… Regression is a supervised learning model for forecasting distinct values. Its same important
framework Support Vector Regression because it … IoT-enabled air quality predictive models …
framework Support Vector Regression because it … IoT-enabled air quality predictive models …
Urbanization and regional air pollution across South Asian developing countries–A nationwide land use regression for ambient PM2. 5 assessment in Pakistan
… of transport in urban air quality in Pakistan was discussed. … an overall atmospheric condition
for each day as it is relatively … First, the resultant land use regression model could be used …
for each day as it is relatively … First, the resultant land use regression model could be used …
A review of air quality modeling
… in air pollution estimation are land-use regression (LUR), machine learning, and hybrid
methods. In addition, when incorporating LUR methods with traffic variables, it … regression model. …
methods. In addition, when incorporating LUR methods with traffic variables, it … regression model. …