New vistas of fuzzy methods in real life application

In the current era of pervasive digitalization, the 7 demand for automation of nearly all spheres of human 8 life has become unprecedentedly high. Automation of 9 routine processes make it possible to achieve higher 10 performance, lower costs and effort on their manual 11 implementation, along with a more viable realloca12 tion of resources and labor contribution. To achieve 13 automation in many aspects of human life, it is nec14 essary to deal with real information. In terms of 15 automated information processing, “information is 16 everything which has influence on the assessment of 17 uncertainty by an analyst. This uncertainty can be 18 of different types: data uncertainty, nondeterminis19 tic quantities, model uncertainty, and uncertainty of 20 a priori information. Measurement results and obser21 vational data are special forms of information. Such 22 data are frequently not precise numbers but more or 23 less non-precise, also called fuzzy” [3]. Operating 24 such kind of imprecise and noisy data requires the 25 establishment of a flexible and adaptive approach 26 to information processing and the development of 27 methodologies to enhance the ability to manage com28 plicated optimization and decision making aspects 29 involving non-probabilistic uncertainty with the rea30 son to understand, develop, and practice the fuzzy 31 technologies to be used in fields such as economic, 32 engineering, management, and societal problems [1]. 33 The idea of fuzziness in the field of mathemat34 ics, Information technologies, and engineering dates 35