Current and Emerging Deep Learning Methods for Flood Simulation - Li, Baiqiang; Gao, Yuan (International Journal of Computer Science and Information Technology, 2024)
In today's world, the development of flood simulation technology is crucial for urban planning and disaster management. However, traditional flood simulation methods are often constrained by the complexity of terrain and meteorological changes, making it difficult to accurately predict the occurrence and impact range of floods. In order to overcome these challenges, the introduction of deep learning technology has brought new ideas and possibilities for flood simulation. By using deep learning models to learn and analyze a large amount of flood data, researchers can more accurately predict the occurrence time, intensity, and impact range of floods, providing strong support for urban planning and emergency response. This article summarizes and discusses traditional flood simulation methods and deep learning based flood simulation methods, and provides prospects for future development.