Ontology of Mathematical Modeling Based on Interval Data

Autor: Mykola Dyvak, Andriy Melnyk, Artur Rot, Marcin Hernes, Andriy Pukas
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Complexity, Vol 2022 (2022)
Druh dokumentu: article
ISSN: 1099-0526
DOI: 10.1155/2022/8062969
Popis: An ontological approach as a tool for managing the processes of constructing mathematical models based on interval data and further use of these models for solving applied problems is proposed in this article. Mathematical models built using interval data analysis are quite effective in many applications, as they have “guaranteed” predictive properties, which are determined by the accuracy of experimental data. However, the application of mathematical modeling methods is complicated by the lack of software tools for the implementation of procedures for constructing this type of mathematical models, creating an ontological model that operates by the categories of the subject area of mathematical modeling, regardless of the modeling object proposed in this article. This approach has made it possible to generate tools for mathematical modeling of various objects based on the interval data analysis for any software development environment selected by the user. The technology of creating the software on the basis of the developed ontological superstructure for mathematical modeling using the interval data for different objects, as well as various forms of user interface implementation, is presented in this article. A number of schemes, which illustrate the technology of using the ontological approach of mathematical modeling based on interval data, are presented, and the features of its interpretation when solving environmental monitoring problems are described.
Databáze: Directory of Open Access Journals