AN ANALYTICAL APPROACH TO MULTI-CRITERIA CHOOSING TECHNOLOGICAL SCHEME FOR INFORMATION PROCESSING
DOI:
https://doi.org/10.15588/1607-3274-2025-4-18Keywords:
information processing, Technological scheme, End information product, Multi-criteria analysis, OWA operatorAbstract
Context. Today, effective information processing is critically important for making strategic, tactical, and operational management decisions. The increasing volumes of information and the need for its rapid analysis necessitate the development and implementation of new methods for multi-criteria choosing technological schemes for information processing. The application of analytical approaches, such as the Ordered Weighted Averaging (OWA) method, allows for the improvement of the quality of final information products, which is relevant for analysis and research in various fields.
Objective. The aim of the research is to develop an analytical approach to multi-criteria choosing an information processing technological scheme using the OWA operator.
Method. The paper uses an analytical approach based on the multi-criteria decision-making method. Specifically, the Ordered Weighted Averaging (OWA) operator is applied, which allows taking into account the weight coefficients of the criteria and their
ranking significance to determine the optimal information processing technological scheme.
Results. The research results show that the application of the OWA operator effectively aggregates the evaluation of alternatives and selects the technological scheme that best meets the specified criteria for the quality of the end information product. The conducted experiments confirmed the effectiveness of the proposed approach in evaluating alternative information processing schemes.
Conclusions. The proposed approach to multi-criteria selection of a technological scheme for processing intelligence data allows for improved quality of the end information product and considers the importance of various criteria. Further research could be focused on the development of automated decision support systems taking into account the metadata of intelligence data.
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