The final model introduces time-dependent aspects by employing system identification techniques.
The model introduces the time decay factor to solve the problem that the trust dynamic change over time, taking into account different transaction amount given different weights, it designs the direct trust calculation method based on service attributes and combining weights, reflecting the direct trust timeliness, rationality.
The model introduces a time allocation step, suggests better approaches in steps such as trip distribution and mode choice, and improves the connections among each model.
Trajectory model [3] introduces time-varying covariance modeling to capture temporal evolutions of speech features.
The LS model introduces a single time constant to dictate the relaxation of thermal propagation, as well as the rate of change of strain rate and the rate of change of heat generation.
In model (1.3), we introduce time delay due to the gestation of the predator.
The flexible reservation model introduces a flexible interval for starting time for advance requests to support request scheduling.
The model introduces considerations about non-linearity of time, path dependency and multi-causality.
When an endemic steady state for all infectious diseases is reached (after about 500 monthly time steps), the model introduces HIV infected individuals until the HIV prevalence reaches 1%, which is the prevalence observed in Malawi in 1981 [ 60].
However, our model introduces some stochasticity in the activation times of clones 1 and 2, which are chosen from a uniform distribution to emulate the un-synchronized nature of T cell-APC encounters.
Therefore, the approaches, mentioned in section "Continuous time in Boolean modeling: past and present", that introduce time implicitly by adding probabilities to each transition of the transition graph, can be seen as a generalization of the definition of γ(S).
