Distributed computer system for monitoring and control of thermoacoustic processes

Recurrent approximation as the tool for expansion of functions and modes of operation of neural network

“…The introduction of indicators [16,18], which are formed by the comparative rules, demonstrates that they can be used for the formation of productive rules. Development of the systems for initial processing of data using RANN [16,18], that has recently been implemented in the automated systems [7][8][9], in industries [12][13][14] that are rapidly readjusted, and surveillance systems [14], necessitates further development of rapid methods [19][20][21][22] of instantaneous learning and qualitative analysis and the methods of formation of results -conclusions based on it [7,8,10,[19][20][21][22]. As demonstrated in articles [15][16][17], new types of representation of continuous signal with a simultaneous application of the indicators -vectors [16] and recurrent approximation [15] opens new approaches to diagnosing [15,16] and creation of RANN.…”

“…At the same time, at present there are successfully operating systems of expert functional diagnosis of complex objects, for example [7,9]. There are attempts at constructing models of dynamic processes based on the networks of different types [2,3] created on the methods of conventional and fuzzy logic [4,[8][9][10][11][12][13][14]. Modeling of the systems is conducted, which include non-stationary objects [3,[8][9][10], including the GPSS environments [3].…”

“…Modeling of the systems is conducted, which include non-stationary objects [3,[8][9][10], including the GPSS environments [3]. They examine and analyze the processes of formation of databases [9] and knowledge bases [12][13][14], formation of productive rules and conclusions based on the Sugeno-Mamdani algorithms and the use of fuzzy neural networks for identification and control of weakly formalized objects, using the Sugeno-Mamdani-Kang network [8]. However, as it is generally known, one of the tools for coordination, which in its initial essence provides coherence of functions of the components of a system and synchronization of objectives as a single entity, is a neural network.…”

Criteria for the evaluation of model's error for a hybrid architecture DSS in the underwater technology ACS

“…As evidenced by studies over the past 30 years [16][17][18][19][20][21][22][23][24][25], the development and implementation of DSS in underwater technology and other sectors is based on such principles as [15,[16][17][18][19][20][21][22][23][24][25]: flexibility, adaptivity and hybridity in the architecture for heterogeneous elements, including the systems of effect modeling and prediction of their behaviour under the influence of external factors. Controlling the systems, in which measuring devices, mechanisms, drives, subsystems that exchange streams of continuous and digital signals [15] operate simultaneously, should be performed based on the experience of DSS implementation in other sectors, for example [15,[17][18][19][20][21][22][23][24][25]. According to papers [5, 21-23, 28, 29], an important element that enables the functioning of DSS regardless of the area of application is the criteria for the qualitative and quantitative selection of alternatives.…”

Realization of the paradigm of prescribed control of a nonlinear object as the problem on maximization of adequacy

“…Cybernetic approach [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15] and formation of prescribed behavior [41][42][43][44][45], as the new paradigm of controlled interaction and information connection, is becoming increasingly common. Its realization [2, 8, 10, 11-13, 21, 25, 28, 29, 31, 34, 48], observed in the living organisms, by being artificially copied, is also formed when designing machines [1, 5-8, 15-18, 31-32], in the integrated computer systems [14][15][16][17], organized production facilities and public structures [9,[15][16][17][18][19][20]. In the recent decades, it has emerged as the necessity of engineering practice [21-26, 40-46, 49-51].…”