… Dynamic models Dynamic prediction models have been proposed as a potential solution
to calibration drift and to allow prediction models to evolve simultaneously with the healthcare …

A review of black-box models for short-term time-discrete prediction of the silicon content of
hot metal produced in blast furnaces is presented. The review is primarily focused on work …

… modeling real-time and historic data for travel time prediction. Factors that would affect the …
is to develop dynamic models that can efficiently predict travel times with real-time and historic …

… In other words, these terms would be very important for very long-range predictions, but
they should have very little significance if t is not too large. In any case the range of time over …

… t and then combining it with the observed data at time t+1 … time t as the prior distribution for
time t+1 in the prediction equation. Inherent to this modeling approach is a vector of dynamic …

… arrival time prediction, the models developed with historic data cannot respond to dynamic …
networks (ANNs) for the dynamic prediction of vehicle arrival and departure times. In addition, …

… This study develops a dynamic bus arrival time prediction model using the data collected by
… which the prediction error in the most recent observation is used to optimize the arrival time …

… ► We present a Bayesian inference-based dynamic model to predict freeway travel times.
► The method provides the distribution of predicted travel times and their confidence intervals…

… We will first develop the methodology for covariates with time-varying effects. In section 2, …
time point tLM to the prediction horizon thor is an easy and valid way of making prediction …

… It is more than evident that such prediction tools would be … , we consider dynamic
subject-specific predictions, and … In particular, under a general definition of prediction rules, we …