Monitoring water quality parameters in rivers is of critical importance for decision makers and researchers. However, difficulties such as missing data, test values exceeding certain limits and parameters that are not measured but need to be monitored are among the main problems in monitoring water...

Precise and dependable forecasting of Particulate Matter 2.5 ( P M 2.5 ) and P M 10 levels hold significant importance for the public's ability to proactively mitigate exposure to air pollution and for informing governmental policy responses. Nonetheless, predicting PM2.5 and PM10 concentrations...

Currently, most of the global population resides in metropolitan areas, where air quality standards are not properly monitored. As a result, people are constantly exposed to air contaminants that exceed the thresholds set by the World Health Organization (WHO). Air quality monitoring system is often...

Air quality prediction is crucial for environmental monitoring and public health. This work presents a new prediction model for air quality prediction using a one-dimensional convolutional neural network (1D- CNN). The proposed model resembles U-Net architecture which is used in image segmentation...