DEVELOPMENT OF METHODS FOR IDENTIFYING THE STATE OF VARIOUS DYNAMIC OBJECTS.

Artificial intelligence technologies are actively used to solve both general and highly specialized tasks. In the process of assessing (identifying) the condition of complex and heterogeneous objects, there is a high degree of a priori uncertainty regarding their condition and a small amount of initial data describing them. The trends of armed conflicts of the last decades and the regularities of the development of information systems, convincingly indicate the need to change approaches to the collection of information from various sources and their analysis. There is a constant transformation of the forms of information presentation and the order of storage and access to various types of data. The problem of integrating disparate sources of information collection into a single information space is also not fully resolved. That is why the issue of improving the efficiency of assessing the state of complex and heterogeneous dynamic objects is an important and urgent issue. The objects of research are heterogeneous dynamic objects. The subject of the research is the identification of the state of heterogeneous dynamic objects. In the research, the method of identifying the state of heterogeneous dynamic objects was developed. The novelty of the proposed method consists in: – taking into account the degree of uncertainty about the state of a heterogeneous dynamic object; – taking into account the degree of data noise as a result of distortion of data characterizing the state of a heterogeneous dynamic object; – reducing computing costs while assessing the state of heterogeneous dynamic objects; – the possibility of performing calculations with source data that are different in nature and units of measurement. It is advisable to implement the mentioned method in specialized software, which is used to analyze the state of complex technical systems and make decisions. [ABSTRACT FROM AUTHOR]