Issue |
E3S Web of Conf.
Volume 524, 2024
VII International Conference on Actual Problems of the Energy Complex and Environmental Protection (APEC-VII-2024)
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Article Number | 03016 | |
Number of page(s) | 6 | |
Section | General Earth Sciences and Energy Resources | |
DOI | https://doi.org/10.1051/e3sconf/202452403016 | |
Published online | 16 May 2024 |
Tools for ranking objects of the mineral resource complex based on ontology
Department of Digital economy, BSTU, 50 let Oktyabrya bul., Bryansk, 241035, Russia
* Corresponding author: m@vdadykin.ru
Mineral resources form the basis for the development of the vast majority of industries. At the same time, most of them are non-renewable. To determine promising exploration activities in conditions of limited human, financial, and sometimes technical resources, it is necessary to take into account a large number of factors when setting exploration tasks for the reproduction of mineral resources. To solve problems with relatively weak formalization, it is customary to use the mathematical apparatus of fuzzy logic in decision support systems. However, it must be based on an ontological model that will contain the interrelationships of the elements of the system and allow you to find implicit relationships between them. In this paper, based on the mathematical apparatus of fuzzy logic and the Mamdani method, it is proposed to form an ontology of geological and economic monitoring in relation to a mineral resource facility (MRF), an industrial raw materials hub (IRMH) and an administrative entity. As a result, using the Reasoner component built into Protege, indicators of geological and economic monitoring, taxonomic units and the frequency of information collection for designing a decision support system in the geological industry were determined. It is possible to create such a convergence, taking into account the heterogeneity of data storage systems, on the basis of an ontological model. The advantage of using ontology is the high level of this tool flexibility, taking the form of heterogeneous data integration within a single storage system. This article attempts to use ontological models framework together with artificial intelligence for the geological subject area in terms of solid minerals, particularly common ones, and ground waters.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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