AI and Neural Networks in Predicting Natural Disasters

Abstract

Predicting natural disasters such as earthquakes, hurricanes, and floods is critical for disaster preparedness and response. Artificial intelligence (AI), particularly neural networks, has shown significant potential in improving the accuracy and timeliness of disaster prediction models. This article explores the application of AI and neural networks in predicting natural disasters, focusing on their ability to analyze complex datasets and recognize patterns that are indicative of impending disasters. We examine the use of deep learning models, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), in disaster prediction, and discuss the challenges and ethical considerations associated with their deployment.