An Approach to Development of a Mathematical Model for Determination of Monitoring Objects Using Informativeness of thei
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AN APPROACH TO DEVELOPMENT OF A MATHEMATICAL MODEL FOR DETERMINATION OF MONITORING OBJECTS USING INFORMATIVENESS OF THEIR MONITORING INDICATORS O. Iliashov1† and V. Komarov1‡
UDC 621.391
Abstract. The paper proposes an approach to development of a mathematical model for determination of monitoring objects using informativeness of their monitoring indicators. The possibility of calculating informativeness of an individual monitoring indicator has been investigated and lines of further research have been determined in terms of calculating the possibility of monitoring source (object) recognition error depending on relative informativeness of the signature and a priori probability of monitoring sources (objects). Keywords: monitoring indicator, signature, informativeness of a monitoring indicator. INTRODUCTION Due to intensive development of information technologies, the number of monitoring sources (objects) (MSO) in the corresponding fields of human and society activities is steadily growing. Consequently, there is a need for development and application of efficient hardware and software packages for MSO monitoring. For this reason, the top-priority tasks are to develop mathematical models that will allow generating information indicators and signatures on their basis, as well as formalizing the problem and further synthesizing algorithms for decision making on whether the selected MSO matches one of the set images of the sample of its information signature values. Recognition of monitoring objects is complicated by difficulty and labor intensity peculiar to formalization of signatures and monitoring indicators, irregularity of their structure, presence of overlapping object classes. At present, the problems of formalizing the reference description of MSO and of their recognition by the corresponding monitoring indicators are not fully solved [1–3]. PROBLEM STATEMENT The complex reference description of signatures of the corresponding MSO for recognition of their phase states is formalized by introducing probabilities of the image belonging to each of image classes and their probabilistic statistical models. The irregular and fuzzy nature of information indicators and signatures built on their basis, as well as insufficiency of the learning sample, add significant complexity to development of the reference description (signature) using probabilistic statistical models; therefore, it is proposed to apply the informative approach to description of MSO signatures. Suppose that, for objects of three MSO classes (Z1 , Z 2 , Z 3 ), there are two signatures with corresponding 1
Central Scientific and Research Institute of the Armed Forces of Ukraine, Kyiv, Ukraine, [email protected]; ‡[email protected]. Translated from Kibernetika i Sistemnyi Analiz, No. 5, September–October, 2020, pp. 95–99. Original article submitted February 04, 2020. †
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monitoring indicators that allow distinguishing between them: the first signature is Z1 from Z 2 a
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