Explainable deep learning for rainfall prediction: A CNN-XGBoost hybrid approach in the northern region of Bangladesh

Explainable deep learning for rainfall prediction: A CNN-XGBoost hybrid approach in the northern region of Bangladesh

<p dir="ltr">Accurate precipitation forecasting is crucial for evaluating various hydrological processes. This research explores the application of deep learning models for rainfall prediction in the northern region of Bangladesh, focusing on the comparative performance of six models...

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Bibliographic Details
Main Author: Md Safayet Islam (23073187) (author)
Other Authors: Md Shafiuzzaman (23073190) (author), Golam Mahmud (23073193) (author), Nabila Nowshin (23073196) (author), Parisa Reza (23073199) (author), Jahid Hasan (4356820) (author), Md. Faysal Ahamed (21842396) (author), Md Nahiduzzaman (9092546) (author), Mohamed Arselene Ayari (16869978) (author), Amith Khandakar (14151981) (author)
Published: 2025
Subjects:
Environmental sciences
Ecological applications
Environmental management
Information and computing sciences
Artificial intelligence
Data management and data science
Rainfall Prediction
Hybrid Deep Learning Models
CNN-XGB
Explainable AI in Hydrology
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