Abstract
Floods are one of the foremost catastrophic natural disasters, and, thanks to their complex nature, it's tough to make a predictive model. The advanced research works on flood prediction models have contributed to risk reduction, policy suggestion, minimization of the loss of human life, and reduced property damage related to floods. In general, ML algorithms are utilized in the event of prediction systems, to mimic the complex mathematical expressions of the physical processes of floods providing better performance and cost-effective solutions. The MLP model is implemented in this system by calculating accuracy values with examining the confusion matrix parameters. The proposed system analyses the dataset using Multilayer Perceptron Classifier (MLP) algorithm to coach the predictive model, and floods are often predicted.
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