In the last decades, natural fire regimes have experienced significant alterations in terms of
intensity, frequency and severity in fire prone regions of the world. Modelling forest fire …

Forest fires are among the major natural disasters that destroy the balance of forest
ecosystems. The construction of a forest fire prediction model to investigate the driving …

Recently, floods are occurring more frequently every year around the world due to increased
anthropogenic activities and climate change. There is a need to develop accurate models for …

The sustainability of water resource management remains challenging in many regions
around the world. Yet while the significance of groundwater potential maps in water …

The development of advanced computational models for improving the accuracy of
streamflow forecasting could save time and cost for sustainable water resource …

In this study, the AdaBoost, MultiBoost and RealAdaBoost methods were combined with the
Quadratic Discriminant Analysis method to develop three new GIS-based Machine Learning …

The forest fires is one of the most dangerous disasters to the livelihood planet of earth.
Human intervention into the field of the destruction of nature is another cause of these forest …

The subjective and empirical setting of hyperparameters in the random forest (RF) model
may lead to decreased model performance. To address this, our study applies the particle …

Water supply is a key challenge and priority for achieving sustainable development goals in
many countries. Recognizing areas with groundwater potential is crucial in addressing this …

Forest fires have significant impacts on economies, cultures, and ecologies worldwide.
Developing predictive models for forest fire probability is crucial for preventing and …