Complex Methods of Processing Different Data in Intellectual Systems for Decision Support System

Abstract

The complex methodology for processing different data in intelligent decision support systems is developed. This method is made to increase the efficiency of processing different data in intelligent decision support systems. The complex methodology consists of the following interrelated procedures: different data storing model; different data synchronization algorithm; different data separation algorithm; different data indexing algorithm. The model of storing different intelligence data, which is the basis of the methodology, differs in the presence of templates of intelligence objects and parameter templates of intelligence objects. Templates allow storing both unstructured different intelligence data and structured intelligence data according to a defined pattern, which reduces the time to access the data. In the different intelligence data storage model, a different intelligence data synchronization algorithm, different intelligence data separation algorithm and different intelligence data indexing algorithm are developed. The development of the proposed technique is due to the need to increase the efficiency of processing various information types in intelligent decision support systems with acceptable computational complexity. The proposed method allows increasing the efficiency of intelligent decision support systems through integrated processing of data circulating in them. The proposed method allows increasing the efficiency of information processing in decision support systems from 16 to 20 % depending on the amount of information about the monitoring object.

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

“…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.…”

Development of estimation and forecasting method in intelligent decision support systems

“…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].…”

“…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.…”

“…The difficulty of taking into account the indirect influence of interdependent components under uncertainty. 6. Nonlinear nature of the interaction of objects and processes, non-stochastic uncertainty, nonlinearity of interaction, partial inconsistency and significant interdependence of components.…”

Development of a method of adaptive control of military radio network parameters

“…We present the main NPUC using quantitative characteristics (Table 3). Table 3 NPUC for selection of the RCD operating mode For each of the modes, rational values of the signal parameters, where the initial input of the RCD and the communication channel parameters, rational values of the parameters for each of the modes are selected, as indicated in [25,26].…”