Development Issues in Algorithms for System Level Self-Diagnosis

Abstract

The paper deals with the problem of developing probabilistic algorithm for system level self-diagnosis. The main goal of the suggested algorithm is to minimize the mean time of its executing. The algorithm is based on the computing of the posterior probability of fault-free state of each system unit. Final decision about unit's state is made on the chosen decision rule. The execution of the probabilistic algorithm is elucidated with the help of simple example and then explained for the case of more complex systems.

Modeling of management of the information potential of complex economic systems under conditions of risk

“…In the theory of modeling the management of the informa tion potential of complex economic systems under conditions of risk, numerous methods and algorithms [2,4,8,14] are found for finding points of the global extremum of functions of several variables for various particular cases. However, no general methods for finding extrema were found.…”

“…In [7,8], the state of approaches and procedures for selecting managerial decisions is analyzed in terms of preferences and limitations of one or a number of variants with known or unknown reaction of the envi ronment, in the form of points of a payment matrix. The location of the selected maximum element determines the decision making option.…”