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