… kernels formulated by data driven approaches can better capture the … traffic prediction in
a given road link (or a freeway) of few miles over a period of few hours. Such data assimilation …

… adjusting the parameters of a simulation model to make it better model a system under study.
… community, the work of Hu 22 offers a tutorial on Bayesian sequential data assimilation and …

… a Bayesian inference methodology to directly update the parameters of the probabilistic model
of bridge traffic … the micro-simulation models, the traffic load effects increase by 5 ∼ 10%. …

… based on Bayesian theory have been applied in some short-term traffic state … -term traffic
flow data are always corrupted by local noises. To improve the accuracy of assimilation models …

… so as to improve the reliability of sequential data assimilation system. The … data assimilation
(DA) method uses Bayesian principles, and new measurements are introduced to the model …

… Our results suggest that while a high observation density is essential for improving the
performance of a model with data assimilation, it is crucial to consider other factors such as the …

… method to improve scalar-dispersion modelling—an important component of air-quality
modelling—by assimilating … To test the data assimilation method in urban conditions, we use the …

… data, bridge structural reliability indices are predicted via a data assimilation method and
Bayesian … various types of data distributions [38], we have decided to enhance the BCDLM by …

… The diversity of ecosystem processes must be better portrayed in CTM in order to improve
model … Fisherian and Bayesian paradigms allow the description with maximum likelihood and …

… Data assimilation is also used to improve the predictability of COVID-19 spreading, see (eg, …
The sequential data assimilation employs the Bayesian filtering process. It adopts a state …