Temporal supervised generative adversarial functional causal model for root cause diagnosis

doi:10.1016/j.jprocont.2026.103652

Temporal supervised generative adversarial functional causal model for root cause diagnosis

2026-02-05

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DOI：10.1016/j.jprocont.2026.103652

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• A new asymmetric directed acyclic causal relationship modeling method derived from functional causal mechanism loss is proposed. • A temporal supervised generative adversarial network is established to effectively extract temporal features used for causal inference. • The proposed TSGA-FCM demonstrates superior performance in root cause diagnosis through validation on both benchmark and real industrial processes.

Keywords:

causal inference

generative adversarial network

root cause diagnosis

temporal features

functional causal model

Temporal supervised generative adversarial functional causal model for root cause diagnosis

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