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Explainable Flood Prediction Using Hybrid Deep Learning, GIS, and Explainable AI for Climate-Resilient Disaster Management

This study proposes an explainable flood prediction framework that integrates GIS, a hybrid LSTM-XGBoost deep learning model, and XAI techniques (SHAP and LIME) to deliver accurate, transparent, and policy-oriented decision support for climate-resilient disaster management.

Original authors: Kazi Abdul Mannan, Al Abdullah

Published 2026-08-04
📖 1 min read☕ Coffee break read

Original authors: Kazi Abdul Mannan, Al Abdullah

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

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