Development of assessment and forecasting techniques using fuzzy cognitive maps

Nowadays, no state in the world is able to work on the creation and implementation of artificial intelligence (AI) in isolation from others. AI technologies are used to solve general and highly specialized tasks in various spheres of society. In the process of assessing (identifying) the state of complex objects and objects of management analysis, there is a high degree of a priori uncertainty regarding their state and a small amount of initial data describing them. At the same time, despite the huge amount of information, the degree of non-linearity, illogicality and noisy data is increasing. That is why the issue of improving the efficiency of assessing the condition of components and objects is an important issue. Thus, the objects of analysis were chosen as the research object. The subject of research is the identification and forecasting of the analysis object. In the research, the evaluation and forecasting method was developed using fuzzy cognitive maps. The features of the proposed method are: ‒ taking into account the degree of uncertainty about the object state while calculating the correction factor; ‒ adding a correction factor for data noise as a result of distortion of information about the object state; ‒ reduction of computing costs while assessing the object state; ‒ creation of a multi-level and interconnected description of hierarchical objects; ‒ correction of the description of the object as a result of a change in its current state using a genetic algorithm; ‒ the possibility of performing calculations with source data that are different in nature and units of measurement. It is advisable to implement the proposed method in specialized software, which is used to analyze the state of complex technical systems and while making decisions.