R&D registration number in UkrISTEI: 0121U107831
What priority area of science and technology does it correspond to: information and communication technologies
Research: applied (scientific development)
Funding source: state budget – general fund of the state budget
Amount of financing: 500 – 1000 thousand UAH. (880.0 thousand UAH)
Year of study start: 2021
The total duration of the study (according to the plan): 2021-2023.
Prospect for further implementation in 2022 – 2023: to be continued as a scientific and technical development
Research level: no analogues in the world
Patent: no
Additional actions requiring further study: additional funding; modern scientific equipment
Participation of the institution in the existing regional targeted and integrated programs: Peter Mohyla Black Sea National University didn’t participate.
Brief description, advantages, further prospects for application.
As a result of the study, the specifics of data processing and expert knowledge processes that occur under the influence of the types of ignorance under consideration, including in conditions of complex forms due to the simultaneous presence of two or more types of ignorance, in particular inaccuracy and incompleteness, uncertainty, fuzziness and inconsistency, are considered. The reasons for their manifestation are revealed. Criteria are defined and a procedure for formalizing the process of their identification is proposed.
A multi-stage procedure for choosing a mathematical apparatus for modeling a certain type of ignorance has been developed, which is based on the synthesis of a system of decision rules for the reasonable choice of a mathematical formalism for modeling an identified type of ignorance (including their possible combinations), based on taking into account a given set of qualitative and quantitative features that uniquely allow and candidate method constraint.
Applied ICT for managing intellectual resources has been developed to support decision-making processes in conditions of incomplete and inaccurate (rough, raw, disordered) data and knowledge of IS and TR, which is based on the proposed mathematical models for analyzing and structuring inaccurate data (knowledge) in the context of group experts . The proposed ICT can be used in solving the problem of classifying coarse (raw) data arrays in the presence of such forms of ignorance as inaccuracy, inconsistency, incompleteness of the initial information (data, knowledge).