Comparative Analysis of Deep Learning Algorithms Integrated with Blockchain for Flood Risk Management

Blockchain technology, known for its decentralized and immutable ledger, is transforming flood risk management by providing a secure and transparent platform for data storage and validation. Combining it with advanced computational techniques like CNNs, MLPs, RNNs, and LSTMs shows promise in improving flood risk management. In this study, these techniques were integrated with blockchain to predict storm severity levels using meteorological data. Results show CNN and LSTM models outperforming MLPs and RNNs, achieving accuracies of around 90.13% and 90.23% respectively. These models, coupled with blockchain, ensure accurate predictions, fostering trust among stakeholders and facilitating collaborative decision-making in disaster management. Further research is needed to optimize performance and explore broader applications in disaster management.