Ontology model of almost periodic data analysis with ordered argument

Abstract

The basic terms, relationships and principles of almost periodic analysis and processing of nonlinear data with ordered argument, in which identification of pure periods is not possible, are considered. To describe the main relationships of almost periodic analysis, ontology models constructed to describe the interaction of resources and data structures. Ontology models of the relations of the main terms of almost periodic analysis proposed, the interaction between processes when using this approach to analyze time series and tropical cyclone photos and videos presented. Based on the proposed ontologies, a class diagram describing the structure of relations and hierarchy of classes of the implemented program of almost periodic analysis built to interact with the user, providing him with convenient systematic functionality for data processing. A description of the sequence of processing of time series data, media data, and identification of almost periodic components in them is given. As a practical implementation of the proposed approach, images of tropical cyclones and time series of annual data on cyclonic energy of typhoons analyzed. The possibilities of displaying the values of characteristic typhoon zones obtained from the results of almost periodic analysis were demonstrated, which allows not only to structurally divide the studied natural hazard into zones of its interaction in space, but also to make a forecast of the dynamics of its development. Forecast estimates of the annual cyclonic energy allowed us to predict in the second half of the 2030s a characteristic data extremum that will change the current annual trend of the dynamics of the accumulated energy of tropical cyclones.