Two types of systems and three types of paradigms in systems philosophy and system science

Abstract

Now it is evident that nature and society have a great number of special systems which very differ from traditional objects (systems) of physics, chemists and engineering. For such special (synergetic-chaotic) systems we propose the special third paradigm and construct five basic properties of (unique) systems and on 13 differences in the methods, basic concepts about such systems. The introduction of such basic properties and differences are presented in the article. We postulate the humanity evolution, dynamic of social and political systems, biosphere of Earth, the human organism and his functional systems and many other systems (Universe at all) have all five such properties and must be described according to special synergetic paradigm. Now the authors presents all these special properties and the special table where the differences between deterministic-stochastic systems (and its theoretical approaches) and the synergetic systems (complexity, self-organization systems) were presented more conveniently.

Chaotic approach in biomedicine: Individualized medical treatment

“…And this "glimmering" involves changes not only in the parameters of the system state vector but also in the dimensionality of the phase space of states, in the meaning of x i (for example, now these x i are the order parameters, but a little later they are no longer the order parameters and other quantities have taken over). It is very complicated to work with such "glimmering systems"; there are no analogs for them in physics or chemistry, since the term "fluctuations" has an already established meaning in the exact sciences and can only be used quite arbitrarily for such systems [1,2,7].…”

Measuring Order Parameters Based on Neural Network Technologies

“…Repetition of the solution for a single task (for example, binary classifi cation) has some analogy to organization of a postural tremor and regulation of cardiac beat-to-beat intervals [2,7,8], when larger orders of magnitude (the fi rst signifi cant fi gures after the decimal point in values of the feature weights) remain unchanged, while for subsequent orders of magnitude a continuously varying nonparametric distribution occurs, which in the general case can have different populations.…”

“…The results obtained have considerable theoretical and practical importance, including for the method of multidimensional phase spaces, considering quasi-attractors: volumes of phase spaces within which the system state vector x i = x(t) = = (x 1 , x 2 , ..., x m ) T executes continuous chaotic motion [1,2]. In an example with a neural emulator, the weights of the dynamic features act as the regulated variables, affecting the mechanisms for the control task in regulation of a tremor and other nonstationary processes in real biological systems.…”

“…Identifi cation of order parameters remains a unique procedure for individual selected tasks. Universal formalization of systems synthesis is lacking at the moment for complex systems, which especially include biosystems [1,2].At the same time, there is a certain class of tasks and systems where such formalization is possible by application of neural network technologies. In recent years, neural emulators have been widely used for identifi cation of the most important diagnostic signs (features) in medicine and biology, but the result obtained with their application is not always unambiguous, and so it has not been worthwhile to use neural emulators for practical purposes.…”

“…Identifi cation of order parameters remains a unique procedure for individual selected tasks. Universal formalization of systems synthesis is lacking at the moment for complex systems, which especially include biosystems [1,2].…”