Modelling stochastic behaviour in simulation digital twins through neural nets

Stochastic Petri Nets: Modelling, Stability, Simulation

On Training Neural Nets through Stochastic Minimization

oij output of unit i of layer j wijk weight connecting the i-th unit of the j-th layer to the k-th unit of the previous layer sigmoidal activation function w a vector representing the network weights Tp(w);Op(w) target value and network output corresponding to the p-th input pattern Ni number of network units in the i-th layer P number of parameters in the network E; E 0 total square error and ...

Stochastic simulation and modelling

Previous research has shown that stochastic models are advantageous tools for representation of the real world. Due to actual spread of fast and inexpensive computational power everywhere in the world, the best approach is to model a real phenomenon as faithfully as possible, and then rely on a simulation study to analyse it. Based on theoretical fundamentals in stochastic modelling and simulat...

Stochastic simulation of HIV population dynamics through complex network modelling

International Journal of Computer Mathematics Publication details, including instructions for authors and subscription information: http://www.informaworld.com/smpp/title~content=t713455451 Stochastic simulation of HIV population dynamics through complex network modelling P. M. A. Sloot a; S. V. Ivanov b; A. V. Boukhanovsky b; D. A. M. C. Van De Vijver c; C. A. B. Boucher c a Section Computatio...

Proxel-Based Simulation of Stochastic Petri Nets

This paper discusses the analysis of stochastic Petri nets using the proxel-based simulation method. The paradigm of the proxel ("probability element") was recently introduced in order to provide a new algorithmic approach to analysing discrete-state stochastic models such as are represented by stochastic Petri nets (SPNs) or queueing systems. Proxel-based simulation is not related to either of...