Abstract
Directly applying Discrete Dynamic Bayesian Networks to time-varying environment is highly complex, it mainly dues to: application environment with mutant characteristics; network structure and parameters needing to have the variation; adapt to the uncertainty of sensor observations. To meet the above requirements, proposing the concept of Flexible Discrete Dynamic Bayesian Network, designing a mechanism of flexible model based on muti-model for the discrete-time systems under mutant environment. Based on the above, applying the Forward algorithm to fulfill Flexible Discrete Dynamic Bayesian Network probabilistic inference thus can be able to use uncertainty observations information to obtain a reliable state estimation.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
