The risk assessment process performs an important role in maintenance decision making,
through structuring the process of identifying, prioritizing, and thereafter formulating effective …

Linear dynamical system (LDS) has established itself as a powerful tool for soft sensing
dynamic industrial processes, which, however, still faces some practically pivotal issues …

Hidden Markov model (HMM) has proven effective for inferential sensing of dynamical and
non-Gaussian industrial processes. However, large-scale process data introduce …

Virtual sensors play an important role in real-time sensing of key quality-related variables in
industrial processes. Linear dynamical system (LDS) paradigm has established itself as a …

The distributed drive autonomous unmanned vehicle (DDAUV) with unknown fault input of
steering system will seriously deviate from the desired path and affect driving safety. This …

Among a variety of virtual metrology models, dynamic generative latent variable models
(DGLVMs) have proven to be an effective tool, owing to outstanding advantages in dealing …

Hidden Markov models (HMMs) for time-series data analysis are attracting wide interests in
industries due to their ability to model the extensively existing dynamics and non …

Humans leverage the dynamics of the environment and their own bodies to accomplish
challenging tasks such as grasping an object while walking past it or pushing off a wall to …

Filtering and smoothing in switching state-space models are important in numerous
applications. The classic family of conditionally Gaussian linear state space models …

Introduction: Recently, with the surge in the availability of relevant data in various industries,
the use of Information Fusion technique for data analysis is increasing. This method has …