Hidden Markov models (HMMs) provide a robust statistical framework for analysing sequential data by assuming that the observed processes are driven by underlying, unobserved states. These models have ...

Drought is a naturally occurring climate phenomenon that significantly affects human and environmental activity, and can be considered one of the most widespread and destructive natural disasters.

This paper proposes a hidden state Markov model (HMM) that incorporates workers’ unobserved labor market attachment into the analysis of labor market dynamics. Unlike previous literature, which ...

Sparse early-stage data limits accurate geological risk assessment, increasing the chance of undetected hazards ahead of the TBM. By integrating borehole-derived information through an observation ...