In the past decades, some desert wetlands have become critical regions for dust production
in the arid and semi-arid regions of the world. Accurate prediction of the number of dusty …

Fuzzy systems are used in modeling and implementation of many real-world applications
operating under an imprecise and uncertain environment. Such systems have effective …

Dust pollution is one of the major environmental crises in the arid regions of Iran and there is
a need to predict dust pollution and identify its controlling factors to help reduce its adverse …

The prediction of particulate matter (PM) concentration around open-pit mining is crucial for
its control. To achieve this, machine learning (ML) techniques have been attempted in PM …

With the increasing application of machine learning (ML) in hydrometeorology, we face the
urge to demystify the ML's black-box nature because it usually does not provide physically …

This study was conducted to evaluate the performance of the support vector regression
(SVR) model with and without applying wavelet transformation for predicting the PM10, PM2 …

Dust storms are natural hazards that affect both people and properties. Therefore, it is
important to mitigate their risks by implementing an early notification system. Different …

This study was carried out to determine whether the changes in dust concentration (DC) in
Iran were attributed to changes in aridity index (AI) from 1990 to 2018. Long-term …

With intense human activity causing constant environmental change, there is a greater need
than ever to have accurate and frequently updated soil information. Traditional soil maps are …

In recent years, climate change has widely affected different ecosystem conditions,
especially natural wetlands across different regions of the world. This study was aimed at …