Application of the ontological approach in the problem of event data generation using simulation models

Abstract

The article describes an application of the ontological approach to solving the problem of generating event data coming from the logs of simulation experiments. Currently, as part of the scientific direction Intelligent analysis of processes, methods and algorithms are being developed that allow solving machine learning problems in relation to event data. Simulation modeling can play an important role in the formation of training samples. However the experimental results of simulation in the form of logs of a certain structure must be brought to the form of event logs as they are understood in the intellectual analysis of processes. This paper provides a statement of the problem for forming an ontological resource that makes it possible to generate an event log based on the results of simulation experiments with a discrete-event model in which requests for processing are presented in the form of agents. A formal description of the domain ontology and an algorithm for its redefinition based on the log data of the simulation model are given. As an object of simulation the paper proposes to consider a hierarchical decision-making system, which receives tasks of varying complexity. The level of complexity of tasks is used for choosing the level of hierarchy at which this task needs to be solved. The architecture of the developed ontological system is given, as well as the structure of concepts with the corresponding semantic relations and sets of instances.