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Explainable Neuro-Fuzzy Prediction for Trustworthy Decision-Making in Maritime

arXiv · AI, language, vision and robotics · article · Sep 21, 2026 · UTC

Predicting when maritime systems require maintenance can be critical, avoiding hazards and costly consequences. To address this problem, this paper proposes an explainable decision-making framework that integrates a neuro-fuzzy prediction model with a two-stage explainable component. The first stage of this component produces feature-attribution explanations, using gradient-based saliency maps, and the second stage extracts local rules using a fuzzy decision tree. The proposed framework is generic and can be integrated into any deep learning-based approach, rendering it explainable. To the bes

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