The project aims to develop and investigate new techniques in contemporary mathematical areas that deal with aggregation operators and approximative equation solving. The main objective is to obtain advanced techniques applicable to digital operational research. A particular interest will be problems in Digital Forensics. The proposed research combines classical computational intelligence techniques originating in mathematical structures with new procedures based on modern mathematical tools from Fuzzy Set Theory and Decision-Making Theory, such as aggregation operators, fuzzy measures, and fuzzy relation equations.

Therefore, the central concept of the proposed project consists of developing new techniques in the broader area of Fuzzy systems and Decision-making oriented to problems of digital operational research, with particular attention dedicated to Digital forensics.  In this context, the team will extend methods that have already been obtained in the previous research of the project members and construct user-friendly models based on various types of aggregation operators. The obtained methods will be applied to problems that appear in digital media due to the lack of information, corrupted data, or errors, as well as to problems of data ranking. The main expected result of the proposed project is the development of new nonstandard mathematical methods of digital operational research constructed in fuzzy logic, fuzzy systems, fuzzy relational equations, decision theory, fuzzy measures, and aggregator operators’ surroundings. The obtained results of the project will be published in journals of the highest category and presented at the leading conferences in this area.

The expected impact is on the scientific community, theory and application, and the Digital forensics practice. The proposed project is closely related to the action Digital Forensics Evidence Analysis via Intelligent Systems and Practices CA17124 (Digforasp), funded by the COST, and joins experts from several European countries. Although the CA17124 now ended, research and collaborations established within this action are foreknown to continue, and this project has a crucial part in this continuation.