Neural Networks for Predictive Modeling in Disaster Management

Abstract

Neural networks have shown great potential in predictive modeling for disaster management. By analyzing large and complex datasets, these AI models can provide accurate forecasts of disaster events, helping authorities to make timely decisions for effective response and mitigation. This article explores the use of neural networks, particularly deep learning techniques, in predicting natural disasters such as earthquakes, floods, hurricanes, and wildfires. We discuss various applications, including early warning systems, resource allocation, and evacuation planning, as well as the challenges and ethical considerations in the use of AI in disaster management.