A trusted model with macroscopic forecasting function based on Markov framework process

Internet is a nonlinear dynamic system. The former research methods about trusted is mainly focusing on addition, therefore the maneuverability is not strong. In this paper, we propose a trusted model with macroscopic forecasting function, based on Markov framework process. Giving the key definitions for the forward and backward equations to compute the probability distributions of this kind of processes. Then we get one-dimensional distributions of the processes. At the same time, this paper presents trusted model with compound Poisson process to illustrate the implementation of the model and iteration algorithm. Finally, simulation experiments are proposed about how to create and apply the model. This research shows that concerning about the influence of trust, reputation, award and penalty. The model can be resolved the lack of dynamic adaptability for environmental varieties in the classical model. Copyright © 2011 Binary Information Press.