Nelvinebi / hybrid-ai-lstm-xgboost-interpretable-water-quality-predictionView on GitHub
A hybrid AI system combining LSTM, XGBoost, and K-Means to predict and interpret water quality using limited data. It computes WQI, identifies key pollution drivers, and reveals contamination patterns, enabling accurate, explainable, and scalable environmental decision-making for data-scarce regions like the Niger Delta.
11Apr 8, 2026Updated last week

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