Integration of Tight Quantifi ers into the System for Checking Consistency of Expert Evaluations

This paper discusses the integration of tight quantifiers into a system for checking the consistency of expert evaluations, significantly enhancing the system’s ability to analyze various scenarios. Existential and universal quantifiers enable the processing of more complex logical expressions, increasing both accuracy and flexibility. This approach allows for consideration of both individual probabilities of factors and their combinations, which is particularly important for solving complex problems related to risk assessment and strategic management. The paper provides a detailed description of consistency-checking algorithms, including graph-based visualization of relationships between expert evaluations and methods for resolving inconsistencies. Additionally, a modular approach to developing a software system for automating expert evaluation analysis is discussed. The proposed system demonstrates high versatility and applicability in risk management, forecasting, and decision-making tasks, making it a valuable tool for improving prediction accuracy and developing more effective management strategies.

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Publication Details

Journal
Vestnik NSU Series Information Technologies
Published
2025-09-08
DOI
https://doi.org/10.25205/1818-7900-2025-23-2-18-28
Primary Topic
Cognitive Science and Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

Integration of Tight Quantifi ers into the System for Checking Consistency of Expert Evaluations

E. D. Malaeva
Vestnik NSU Series Information Technologies
Cognitive Science and Mapping
article

Integration of Tight Quantifi ers into the System for Checking Consistency of Expert Evaluations

E. D. Malaeva
article en

Abstract

This paper discusses the integration of tight quantifiers into a system for checking the consistency of expert evaluations, significantly enhancing the system’s ability to analyze various scenarios. Existential and universal quantifiers enable the processing of more complex logical expressions, increasing both accuracy and flexibility. This approach allows for consideration of both individual probabilities of factors and their combinations, which is particularly important for solving complex problems related to risk assessment and strategic management. The paper provides a detailed description of consistency-checking algorithms, including graph-based visualization of relationships between expert evaluations and methods for resolving inconsistencies. Additionally, a modular approach to developing a software system for automating expert evaluation analysis is discussed. The proposed system demonstrates high versatility and applicability in risk management, forecasting, and decision-making tasks, making it a valuable tool for improving prediction accuracy and developing more effective management strategies.

Vestnik NSU Series Information TechnologiesVol. 23(2)
Novosibirsk State University (RU)
Openalex Percentile: Top 87%
Cognitive Science and Mapping
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