Flood Prediction Using Machine Learning
Keywords:
Supervised learning, Machine Learning, Floods, XGBoost algorithm and K-Nearest NeighborsAbstract
Flooding is the most common natural disaster on the planet, affecting hundreds of millions of people and causing between 6,000 and 18,000 fatalities every year – of which 20 percent are in India. Reliable early warning systems have been shown to prevent a significant fraction of fatalities and economic damage, but many people don’t have access to those types of warning systems. So, we're building Flood prediction system Based on ML or AI. This advancement of the prediction system provides cost-effective solutions and better performance. In this, a prediction model is constructed using rainfall data to predict the occurrence of floods due to rainfall. The model predicts whether “flood may happen or not” based on the rainfall range for particular locations. Indian district rainfall data is used to build the prediction model. The dataset is trained with various algorithms like K-Nearest Neighbors, XGBoost etc.
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