Year: 2025
Type: article
Abstract: Introduction Floods and landslides rank most among the devastating natural hazards, making accurate prediction critical for minimizing their impacts. Traditional forecasting methods often face Issues based on complex nature of environmental systems. Recently, Machine Learning (ML) techniques have shown notable potential, enhancing predictive accuracy by utilizing big data, sophisticated algorithms, and real-time observations. This paper evaluates the latest progress in ML-based prediction systems for floods and landslides, highlighting popular models, available datasets, and existing challenges. Recently, machine learning (ML) techniques have shown notable potential, enhancing predictive accuracy by utilizing big data, sophisticated algorithms, and real- time observations.
DOI: 10.55041/ijsrem47193
Author: Mrs. Amitha S
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4410154724