Development of complex methodology of processing heterogeneous data in intelligent decision support systems

Zuiev, Pavlo; Zhyvotovskyi, Ruslan; Zvieriev, Oleksii; Hatsenko, Serhiy; Kuprii, Volodymyr; Nakonechnyi, Oleksandr; Adamenko, Mykhailo; Shyshatskyi, Andrii; Neroznak, Yevhenii; Velychko, Vira

doi:10.15587/1729-4061.2020.208554

Cited by 41 publications

(75 citation statements)

References 18 publications

(21 reference statements)

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“…It is proposed to use the proposed method in decision support systems of automated control systems (ACS DSS) for artillery units, ACS DSS for aviation and air defense, as well as ACS DSS for logistics of the Armed Forces of Ukraine. This study is a further development of research aimed at developing methodological principles for improving the efficiency of data processing in special-purpose information systems, published earlier [28][29][30][31][32]. Areas of further research should be aimed at reducing computational costs when processing various data in special-purpose information systems.…”

Section: Discussion Of the Results Of Developing The Methods For Assesmentioning

confidence: 98%

Development of a method for assessing cybernetic security in special-purpose information systems

Drozdov

Zhuravskyi

Salnikova

et al. 2020

EEJET

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Section: Discussion Of the Results Of Developing The Methods For Assesmentioning

confidence: 98%

Development of a method for assessing cybernetic security in special-purpose information systems

Drozdov

Zhuravskyi

Salnikova

et al. 2020

EEJET

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“…This research is a further development of research aimed at developing methodological principles for improving the efficiency of information and analytical support, published earlier [2,[4][5][6].…”

Section: Discussion Of the Results Of Developing The Estimation And Forecasting Methodsmentioning

confidence: 99%

“…Analysis of the experience of creating intelligent DSS shows that the most promising is an information technology based on neural network modeling [1][2][3][4][5][6][7][8], in particular on the application of an evolutionary approach to the construction of artificial neural networks (ANN) [2][3][4][5][6][7]. ANN allow processing various types of data, adapting their structure to the type and amount of input data, thereby increasing their own productivity.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Development of estimation and forecasting method in intelligent decision support systems

Mahdi¹,

Shyshatskyi

Prokopenko

et al. 2021

EEJET

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The method of estimation and forecasting in intelligent decision support systems was developed. The essence of the method is the analysis of the current state of the object and short-term forecasting of the object state. Objective and complete analysis is achieved by using improved fuzzy temporal models of the object state and an improved procedure for processing the original data under uncertainty. Also, the possibility of objective and complete analysis is achieved through an improved procedure for forecasting the object state and an improved procedure for learning evolving artificial neural networks. The concepts of fuzzy cognitive model are related by subsets of influence fuzzy degrees, arranged in chronological order, taking into account the time lags of the corresponding components of the multidimensional time series. The method is based on fuzzy temporal models and evolving artificial neural networks. The peculiarity of the method is the possibility of taking into account the type of a priori uncertainty about the object state (full awareness of the object state, partial awareness of the object state and complete uncertainty about the object state). The possibility to clarify information about the object state is achieved using an advanced training procedure. It consists in training the synaptic weights of the artificial neural network, the type and parameters of the membership function, as well as the architecture of individual elements and the architecture of the artificial neural network as a whole. The object state forecasting procedure allows conducting multidimensional analysis, consideration, and indirect influence of all components of a multidimensional time series with their different time shifts relative to each other under uncertainty. The method provides an increase in data processing efficiency at the level of 15–25% using additional advanced procedures.

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“…Paper [28] reports a comprehensive procedure that improves the speed of processing of different types of data in intelligent systems. The proposed methodology improves the efficiency of intelligent decision-making support systems through the integrated processing of data that circulate in them.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Devising a method to identify an incoming object based on the combination of unified information spaces

Mukhin¹,

Zavgorodnii²,

Kornaga³

et al. 2021

EEJET

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This paper suggests a method to search for an incoming object in order to identify its unambiguously, based on the integration of information spaces into intermediate unified information space. At the same time, the incoming object identification process involves appropriate attributes. This paper describes the process of information object arrangement within a unified information space that forms for a set of dynamically changing objects. It should be noted that each subject in the set collects information about the environment, including interaction with other objects. In the process of forming a unified information space, the information system collects information from data sources that are represented in different formats. The system then converts this information and forms a unified information space, thereby providing users with information about objects. A two-tier system of connections at the global (cloud) and local (fog) levels of interactions has been considered. At the same time, it should be noted that a unified information space formation requires the implementation of tools to support the transformation of information objects; that necessitates the implementation of translators ‒ special converters at different levels. A method to combine information spaces into an intermediate unified information space has been proposed; analysis was performed to determine the time and efficiency of the search for incoming objects within it. It was experimentally established that the more parameters that describe an information object, the less the time to identify an object depends on the length of the interval. It has also been experimentally shown that the efficiency of finding incoming objects tends to be a directly proportional dependence while reducing the length of the interval and increasing the number of parameters, and vice versa

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Development of complex methodology of processing heterogeneous data in intelligent decision support systems

Cited by 41 publications

References 18 publications

Development of a method for assessing cybernetic security in special-purpose information systems

Development of a method for assessing cybernetic security in special-purpose information systems

Development of estimation and forecasting method in intelligent decision support systems

Devising a method to identify an incoming object based on the combination of unified information spaces

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