Applying the Theory of Multi-Operations to Building Decision-Making Systems with a Large Number of Uncertainties
This article is devoted to the practical application of multi-operations theory to the construction of decision-making systems and the description of the subsequent research results. Unlike classical multi-valued and fuzzy logic, where events are described by only two logical values, namely, “true”...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/12/23/3694 |
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| author | Sergey Todikov Yulia Shichkina Nikolay Peryazev |
| author_facet | Sergey Todikov Yulia Shichkina Nikolay Peryazev |
| author_sort | Sergey Todikov |
| collection | DOAJ |
| description | This article is devoted to the practical application of multi-operations theory to the construction of decision-making systems and the description of the subsequent research results. Unlike classical multi-valued and fuzzy logic, where events are described by only two logical values, namely, “true” and “false”, when there are various types of uncertainty between these two states, the theory of multi-operations can be used to describe events using a larger number of logical values for the uncertainties between these states. This article demonstrates a new approach to processing input information using rank 3 multi-operations, i.e., considering input information for a set of three logical values and five values of uncertainty. This approach allows for saving time and resources when forming a subject area model for decision-making systems and when working with specific users. The application of this approach is illustrated in the article by using the example of determining the area of human disease. When testing this system, which is built on the basis of rank 3 multi-operations, we show that applying multi-operations theory allows for significant expansion of the range of accepted decisions; this makes the system more flexible for the construction of human–machine interfaces and organizes the integration of efforts in the development of humans and machines with a common goal. |
| format | Article |
| id | doaj-art-ea2ca3642a3346329ac5fcf9cd985595 |
| institution | DOAJ |
| issn | 2227-7390 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-ea2ca3642a3346329ac5fcf9cd9855952025-08-20T02:50:38ZengMDPI AGMathematics2227-73902024-11-011223369410.3390/math12233694Applying the Theory of Multi-Operations to Building Decision-Making Systems with a Large Number of UncertaintiesSergey Todikov0Yulia Shichkina1Nikolay Peryazev2Department of Computer Science and Engineering, Saint Petersburg Electrotechnical University “LETI”, Saint Petersburg 197376, RussiaDepartment of Computer Science and Engineering, Saint Petersburg Electrotechnical University “LETI”, Saint Petersburg 197376, RussiaDepartment of Computer Science and Engineering, Saint Petersburg Electrotechnical University “LETI”, Saint Petersburg 197376, RussiaThis article is devoted to the practical application of multi-operations theory to the construction of decision-making systems and the description of the subsequent research results. Unlike classical multi-valued and fuzzy logic, where events are described by only two logical values, namely, “true” and “false”, when there are various types of uncertainty between these two states, the theory of multi-operations can be used to describe events using a larger number of logical values for the uncertainties between these states. This article demonstrates a new approach to processing input information using rank 3 multi-operations, i.e., considering input information for a set of three logical values and five values of uncertainty. This approach allows for saving time and resources when forming a subject area model for decision-making systems and when working with specific users. The application of this approach is illustrated in the article by using the example of determining the area of human disease. When testing this system, which is built on the basis of rank 3 multi-operations, we show that applying multi-operations theory allows for significant expansion of the range of accepted decisions; this makes the system more flexible for the construction of human–machine interfaces and organizes the integration of efforts in the development of humans and machines with a common goal.https://www.mdpi.com/2227-7390/12/23/3694intelligence systemproperty of explainabilitytheory of multi-operationssystem of inclusions |
| spellingShingle | Sergey Todikov Yulia Shichkina Nikolay Peryazev Applying the Theory of Multi-Operations to Building Decision-Making Systems with a Large Number of Uncertainties Mathematics intelligence system property of explainability theory of multi-operations system of inclusions |
| title | Applying the Theory of Multi-Operations to Building Decision-Making Systems with a Large Number of Uncertainties |
| title_full | Applying the Theory of Multi-Operations to Building Decision-Making Systems with a Large Number of Uncertainties |
| title_fullStr | Applying the Theory of Multi-Operations to Building Decision-Making Systems with a Large Number of Uncertainties |
| title_full_unstemmed | Applying the Theory of Multi-Operations to Building Decision-Making Systems with a Large Number of Uncertainties |
| title_short | Applying the Theory of Multi-Operations to Building Decision-Making Systems with a Large Number of Uncertainties |
| title_sort | applying the theory of multi operations to building decision making systems with a large number of uncertainties |
| topic | intelligence system property of explainability theory of multi-operations system of inclusions |
| url | https://www.mdpi.com/2227-7390/12/23/3694 |
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