Glushenkova I. Methods, models and information technologies for state estimation of spatially distributed objects

The thesis is devoted to developing methods, models and information technology assessment states of complex spatially extended objects, taking into account the deterministic, stochastic and uncertain process character. First hybrid model estimation of spatially distributed objects: are proposed and validated, which integrates advanced fuzzy colored Petri nets model of deterministic, probabilistic and fuzzy logic knowledge bases and manifestations of their interactions, thus enhancing the reliability of decision making while reducing the dimension of the model by color function and mapping function. The method of setting the parameters of membership functions of fuzzy knowledge bases developed further, that basing on interval many-valued logic. It is reduces the computational complexity and time settings of functions by focusing computational procedures for selected classes of linguistic variables terms. Improved method for setting the parameters of membership functions that can significantly reduce the computational complexity of the membership functions. Improved method for many-step analysis of the state space model, which includes changing the state space of dynamic objects. This improves the reliability and adequacy of resources assessment. The effectiveness of the proposed solutions is confirmed by experiment with real objects.