|
|
|
AUTHOR(S): Albert Voronin, Alina Savchenko
|
|
TITLE |
 PDF |
|
ABSTRACT In the hierarchy of system theories, the top level is occupied by synergetics – the science of cooperative processes [1,2]. This is an integral science that allows us to move to a holistic understanding of nature, technology and society based on a single synergetic concept. Unlike general systems theory, synergetics studies cooperative, coherent and self-consistent processes that arise in complex systems. If cybernetics develops management methods in which the system functions in a predetermined manner to achieve a goal, then synergetics organizes a process characterized by self-government and self-organization in accordance with the goal. Here, complex processes develop not under centralized influences, but through the collective interaction of components. Cooperation of components allows the use of reserve capabilities of the system and significantly increases the degree of emergence (system effect). Of course, the transition to a holistic, synergetic concept requires new scientific and applied research that reflects cooperative, synergetic phenomena in the relevant subject areas of knowledge [1]. Therefore, the problem considered in this article is relevant. |
|
KEYWORDS synergetics, data complexation, degrees of freedom reducers, degrees of freedom discriminators, functional system, expert assessments |
|
|
|
Cite this paper Albert Voronin, Alina Savchenko . (2025) Data Complexation: Synergic Methods. International Journal of Computers, 10, 215-219 |
|
|
