Public infrastructures are not only subject to terrorist attacks but also to risks of increasing frequency and magnitude related to extreme weather conditions, natural disasters, physical threats, climate change, and human errors. Modelling and forecast of such disasters require the development and use of mathematical and statistical models. Thus, reliability assessment for infrastructures is also a primary area of concern. Dynamic reliability assessment and preventive maintenance is important for many infrastructures. Real time degradation modelling has recently gained much attention in the literature. With advances in technology nowadays systems can be monitored by many sensors and this generates high dimensional data in real time. It is desirable in
such cases to develop stochastic methods to anticipate failure and to take timely preventive measures by the real time tracking of degradation. One way to achieve this is to develop efficient computational methods like particle filtering to process real time data and recent advances in Bayesian methods can play an important role here.
Questions: email email@example.com