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Therefore, we propose a RCM based on stochastic principle to understand the traffic behavior in a better way.
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NORMA is based on stochastic gradient descent.
Reliability analysis is based on stochastic discrete event models like stochastic Petri nets.
Our mechanism is based on stochastic datagram relocation.
The algorithm is developed based on stochastic finite-element method.
KF technique makes predictions based on stochastic and dynamic structures.
However, several simplifying assumptions were made in the calculations based on stochastic differential equations.
Moreover, the VQ algorithm is based on stochastic gradient descent optimizations.
Simulation studies of XCI, based on a stochastic principle, indicate that XCI counting and choice can be mimicked when using a probability for an X chromosome to be inactivated, in which the probability is dependent on a nuclear XCI-activator concentration acting at differential threshold levels for X chromosomes with specific Xce alleles.
Then, the adjoint equation and maximum condition of the partially averaged control problem are derived based on the stochastic maximum principle.
Instead of carrying a small noise analysis, a multiscale approach based on the stochastic averaging principle [2] can be a powerful tool to unravel subtle interplays between noise properties and non-linearities.
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