A modular pipeline combining MLP prediction, LIME/SHAP explanations, fidelity/stability metrics, and LLM natural-language summaries is demonstrated on power-system fault and building-energy datasets.
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An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems
A modular pipeline combining MLP prediction, LIME/SHAP explanations, fidelity/stability metrics, and LLM natural-language summaries is demonstrated on power-system fault and building-energy datasets.