Author

Tian-Wei Mu

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#artificial intelligence Review Oct 2026

HydroJEV: A one-second, training-free screen for cyber-attack and fault attribution in water distribution networks

When a SCADA alarm is raised in a water distribution network, operators must decide quickly whether it reflects a cyberattack, a physical fault, a normal transient or a faulty sensor. Supervised classifiers need labelled incidents that utilities rarely have, and frontier large language models (LLMs) take tens of second...

Tian-Wei Mu, Sheng-Yan Jiang, Ming-Zhe Yuan et al. · 0 citations

#artificial intelligence Review Aug 2026

Verifiable abstention makes AI leak diagnosis accountable in urban water distribution networks

A pressure-information limit is quantified and used to recast localization as selective, evidence-gated decision-making and Observability limits with machine-checkable abstention enable auditable utility intervention.

Tian-Wei Mu, Yue Wang, Ming-Zhe Yuan et al. · 0 citations