Efficiency evaluation of methodical and algorithmic support of a special purpose decision support system
To eliminate information overload when assessing the state of air and space radio control objects for decision-making, we use methodological support and classification algorithms of decision support system (DSS) objects of an automated control system (ACS) for special purposes. The paper presents a method for efficiency evaluation of algorithmic support of a special purpose ACS DSS. The method is based on artificial generation of input data, as well as data representing a set of all possible values based on an exhaustive enumeration in the form of generating programs of random objects and random areas. This approach uses the analysis of the relative location of regions in a parametric space, which is a catalog of reference values. In this approach, there is no need to compare object parameters with the parameters of all catalog classes. After finding the first input into an area, we consider the possibility of getting the analyzed object into those areas that have intersections with the area in which the object has already got. The obtained experimental results of evaluation of a general computing labor intensity of the special-purpose ACS DSS when classifying the objects using a combined method is, on average, two times lower than the basic classification method. The obtained result is particularly relevant in the classification of air and space radio engineering control objects under conditions of intensive realtime data entry.