harsh-sql / flood-detection

This repository has been created as a part of our 7th semester project on Data Science where we choose to detect the flood based on various algorithms.

Flood-Detection

• Project Name : Innovative Environmental Monitoring & Early Alert System

• Floods, one of the most devastating natural disasters, cause widespread damage to property, infrastructure, and life. Accurate flood prediction is crucial for disaster preparedness and mitigation. Traditional methods of flood prediction rely on physical models and historical data, but these methods can be inaccurate and time-consuming. Machine learning (ML) has emerged as a powerful tool for flood prediction, offering a data-driven approach that can capture complex relationships between various factors and flood occurrence.

• This repository has been created as a part of our 7th semester project on Data Science where we choose to detect the flood based on various algorithms.

• There is a paper that investigates the application of five ML algorithms: KNN, LR, DT, RF, and EL, for flood prediction. The algorithms are evaluated using a dataset of historical rainfall and flood data from Kerala, India.