Modern studies in the field of environment science and engineering show that deterministic
models struggle to capture the relationship between the concentration of atmospheric …

The paper presents the screening of various feedforward neural networks (FANN) and
wavelet–feedforward neural networks (WFANN) applied to time series of ground-level ozone …

Environmental processes are highly complex and their understanding involves the analysis
of various quantitative and qualitative parameters (physical, chemical, geographical etc) …

In view of pollution prediction modeling, the study adopts homogenous (random forest,
bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to …

Previous studies indicate that the main cause of air quality deterioration is the concentration
of particulate matter up to 10 µm in size (PM10). So far, however, there has been little …

Airborne particulate matter (PM) is considered to be an essential indicator of outdoor and
indoor air quality. In this study, indoor and outdoor PM 1, PM 2.5, PM 10 concentrations were …

Kolkata has a reputation for being one of the world's most polluted cities, particularly in the
post-monsoon months of October, November, and December. Diwali, a Hindu festival …

The paper analyzes two artificial intelligence methods for particulate matter air pollutant
prediction, namely data mining and adaptive neuro-fuzzy inference system (ANFIS). Both …

Air quality monitoring is one of several important tasks carried out in the area of
environmental science and engineering. Accordingly, the development of air quality …

The concentration of airborne pollutants is rising in recent years. Due to serious health
effects of NO2, SO2 etc. their constant monitoring is important for the policy makers, as it …