THE USE OF MARKOV ALGORITHMS FOR THE STUDY OF l-VOIDS IN BIG DATA OF SOCIO-ECONOMIC SYSTEMS. PART 2

Abstract

The second part of the article is presented. Big data l-voids are considered using the N-scheme of the Markov algorithm. The diagrams of occurrences of l-voids in a semi-Eulerian cycle containing an Euler path, a matroid and an incomplete Fano matroid, minors K3, 3 and K5, an extra large cycle of occurrences are analyzed. An example of reconstructing a fragment of an incomplete Fano matroid with l-voids is considered. Examples are given for independent implementation of the method of filling the artificial intelligence database (AnwM f typeK) DB based on the results of the analysis of l-voids in the N-scheme of the Markov algorithm. The database is populated using a formal language with the alphabet M = litj/abdgckm where litj are terminal elements, abdgckm are non-terminal elements, and the basis of the alphabet is i – initial, t – terminal, j – isomorphic, l-empty morphisms. The p – initial, e – simple, and h – final occurrences of words from the Markov alphabet A are determined. An example of a simplified numbering of occurrence chains is given, which ensures the selection of all objects represented by words in the Markov alphabet A, belonging to “their own” chain of occurrences, as well as all related to chain object. The mechanism of dynamic change of the number-type in the N-scheme of the Markov algorithm is presented, which provides the analysis of the word as an evolving category, as well as the evolution of categories, which includes such a word. It has been established that normal Markov inference is characterized by temporal conditionality and locality. The conclusion is made about the expediency of considering the N-scheme in a distributed computing system. In this case, it is necessary to analyze the diagrams of occurrences of objects that have several designations with words from the Markov alphabet A, in order to identify them and process data from such objects.