Implementation of cognitive perception functions in fuzzy situational control model

Kargin, Anatolii; Panchenko, Sergej; Vasiļjevs, Aleksejs; Petrenko, Tetyana

doi:10.1016/j.procs.2019.01.128

Cited by 9 publications

(2 citation statements)

References 8 publications

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“…The motivation for the implementation of this approach for the identifying the meaning of words is its capacity to produce the independent judgement needed for the supporting the new control systems, since it acts as a necessary link in the development of methodology for the understanding of complex situations and the decision-making process [11,12]. The need for research based on the methods of cognitive linguistics is due to the limitation of existing methods [13][14][15] The effective strategic control for the management of complex systems requires the development of a methodology for the implementation of the cognitive approach and tools that would allow decision-makers to implement the reason-based strategic goal setting procedure [16,17].…”

Section: Research Materials and Methodsmentioning

confidence: 99%

Semantic Modelling for the Communication Mechanism of the Production System

Karlik

Яковлева

Платонов

2021

Knowledge in the Information Society

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The study deals with the application of intelligent management technologies to support communicative mechanisms in the modern production environment based on the analytical tools which apply the cognitive approach, namely, the semantic modelling. It supports the application of the situation analysis for strategic control based on the principle of management metafunctions. The article presents the semantic model of a discrete situational network in the form of a network graph. It is designed to contribute to the implementation of the communicative strategies to facilitate the decision-making under digitalization. The analytical procedure also designed for decision-making on municipal level that is important under tough budget constraints conditioned by the COVID-19 pandemic. The main result of the study is the semantic model of the communicative mechanism of the production system. The proposed intelligent solutions are risk-sensitive because it accounts for the significant exposures. The systematization of the order of interaction under implementation of the cyber-physical systems, production cooperation and communication within the specialization network chain allow to apply the system analysis to the communicative processes that enable information transfer. The article is designed to contribute to the system theory and methodology by application of logical-linguistic analysis and modeling as well as by combining adaptive management and semiotic approach in application to the communicative mechanism of production systems.

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Section: Research Materials and Methodsmentioning

confidence: 99%

Semantic Modelling for the Communication Mechanism of the Production System

Karlik

Яковлева

Платонов

2021

Knowledge in the Information Society

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“…In the fuzzy logic model, the Mamdami algorithm has been applied [2,4] and it consists of the following steps. In the first step, factors or variables are selected that are presented as fuzzy values.…”

Section: Development Of the Intellectual Point Heating Control Algorithmmentioning

confidence: 99%

Development of the Railway Point Electric Heating Intellectual Control Algorithm

Muhitovs¹,

Mezitis²,

Korago³

2020

Transport Problems

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The article reviews and describes the problems of the railway point heating conventional control system considering its structure, simple design, disadvantages and nonconformity. As a solution to the described problem, an innovative and advanced point heating control algorithm is proposed based on Mathlab's Fuzzy Logic Designer module, which will allow control of heating more effectively and intellectually. The tasks for the advanced and intellectual point heating control system were set. The interdependency of different input variables and their weights of the proposed algorithm are shown and described. Conclusions show that the approach of introducing a control algorithm based on Fuzzy Logic will allow to control point heating in a more advanced and efficient wayswitching on and off based on the interdependency of different weather conditions and weather forecast; the input data control system will decide automatically when to switch the heating on and off.

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Spatio-Temporal Data Interpretation Based on Perceptional Model

Kargin

Petrenko

2019

Advances in Spatio-Temporal Segmentation of Visual Data

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Implementation of cognitive perception functions in fuzzy situational control model

Cited by 9 publications

References 8 publications

Semantic Modelling for the Communication Mechanism of the Production System

Semantic Modelling for the Communication Mechanism of the Production System

Development of the Railway Point Electric Heating Intellectual Control Algorithm

Spatio-Temporal Data Interpretation Based on Perceptional Model

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