Author(s)

D. SITNIKOV, O. RYABOV, I. MISHCHERIAKOV & A. KOVALENKO

Abstract

A complex system is considered as an algebraic structure having specific properties that do not allow expressing precisely the meaning of information objects included in the system. An algebraic definition of complexity has been given. the complexity has been considered from two viewpoints. A system can be considered to be a complex one if (a) boundary regions for system’s objects and processes are broad; (b) possibilities for system’s decompositions are limited. difficulties associated with complex system description and decomposition have been discussed in the framework of rough set methodology. A method for extracting salient features of information objects available in the system has been outlined. some theoretical aspects of rough set based analysis of complex systems have been discussed. All the operations designated to obtaining new knowledge or data patterns in complex systems are algebraically described from the viewpoint of algebraic systems including predicates (in particular, finite ones) and operations on them. thus, a system is considered to be complex if there is a great degree of uncertainty in the data and/or there are some serious problems with system’s decomposition.”

Keywords

big data, complex system, knowledge discovery, rough set, system decomposition, uncertainty in data