第五部門：応用数理問題（A)

[S05A-03] Model update and decision making using Particle Filter

*Tomoka NAKAMURA¹, Ikumasa YOSHIDA¹, Takayuki SHUKU² (1. Tokyo City University, 2. Okayama University)

Keywords:Particle Filter, Decision making, Data assimilation, Limit state exceedance probability

In many real problems, predictions by numerical analysis are used to make decisions about whether or not to take measures. There are many uncertainties in the numerical analysis that makes predictions. Data assimilation is a method of reducing prediction uncertainty using observational data. Predicting long term settlement is important for life cycle management of infrastructures constructed on the soft clay ground such as embankments, reclaimed island, etc. This study combines particle filter and reliability estimation for settlement prediction, and shows update of limit state exceeding probabilities according to give observation data. It is demonstrated that the data assimilation and model updates allow for clearer decisions making.