Progress in combustion science and engineering has led to the generation of large amounts
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …

Artificial intelligence has been applied in wildfire science and management since the 1990s,
with early applications including neural networks and expert systems. Since then, the field …

Fire is a recurring event that usually causes a lot of social, environmental, ecological, and
economic damage in different environments. Therefore, machine vision-based fire detection …

The quantitative simulation of forest fire spreading plays an essential role in designing quick
risk management and implementing effective suppression policies. As a preferable …

Wildfires are complex natural events that cause significant environmental and property
damage, as well as human losses, every year throughout the world. In order to aid in their …

This paper presents a hybrid predictive model for forecasting intraday stock prices. The
proposed model hybridizes the variational mode decomposition (VMD) which is a new …

Simulation frameworks are necessary to facilitate decision-making to many fire agencies. An
accurate estimation of fire behavior is required to analyze potential impact and risk. Applied …

The main objective of the present study is to evaluate the risk of wildfire in the highly
suspected potential areas and provide the prevent and mitigative actions using hybrid …

One of the most ubiquitous cause of worldwide deforestation and devastation of wildlife is
fire. To control fire and reach the forest area in time is not always possible. Consequently …

This paper presents the mathematical development of a geospatial model for simulating
wildland fire spread. The Eulerian level set method (LSM), a mathematical technique that …