Jing Zhang

A Novel Time-Varying Failure Risk Assessment Framework for Marine Diesel Engines Integrating Large Language Models and Bayesian Networks

Fault risks in marine diesel engines (MDEs) propagate across coupled subsystems and evolve with component degradation, but existing methods rarely integrate accident narratives, causal structure, and time-varying reliability. This study develops a novel framework that integrates large language models (LLMs), rough–fuzz...