Research Of F-gert Network Model And Their Application Based On Credibility Theory

The GERT network based on classical probability theory has been relatively mature, and its scope of application is very extensive, including almost resource planning, contingency planning, seismic analysis, product development, trial and improvement plans, and many other industries and fields. However, there is also a large number of non-probabilistic uncertainty outside of the probability of uncertainty, such as the fuzzy uncertainty and grey uncertainty. Fuzziness infiltrate into almost all fields of science and technology, and credibility theory is a complete study of the theory of ambiguity. Thus, it has important theoretical value and potential applications to combine the GERT network technology with the credibility theory effectively and establish credibility based on the theory of GERT network technology (referred to F-GERT) .It is the first time extending GERT network study range from the traditional random environment to fuzzy environment. In view of random network with the fuzzy information parameter, a new F-GERT network modeling technique which considers the fuzzy information is proposed in this thesis. Moreover, the moments and moment generating function of F-GERT network are constructed and the important mathematical nature of its four aspects is discussed in detail. On this basis, the simulation algorithm of F-GERT network is studied using signal flow graph principle.Then, it studied the moedl of fuzzy information of the F-GERT network with the number of times repeated questions. The thesis has defined the basic unit of feedback network, multi-feedback network, multi-feedback progressive network, multi-hand feedback network, multi-feedback hybrid networks and fuzzy feedback network, and examined the rules of the network model simplified. On this basis, the number of times to repeat the implementation of ideas for solving based on the number of pairs of repeated F-GERT network, the implementation of the number of algorithms, conditional moment generating function, the process arrival time were studied.Finally, fuzzy equivalent transfer function and equivalent to fuzzy probabilit were determined by the signal flow graph of the topological equations to F-GERT networks. The transfer function was equivalent to fuzzy moment generating function according to the definition of WF function. It anti-derivated the basic parameters of F-GERT network by the equivalent fuzzy moment generating function and designed hybrid intelligent algorithm based on fuzzy simulation and genetic algorithm of F-GERT network model.Numerical tests were given in detail . Through simulating we know that the effect is good.