GENERACJE W SIECIACH BAYESOWSKICH

This paper focuses on the study of some aspects of the theory of oriented graphs in Bayesian networks. In some papers on the theory of Bayesian networks, the concept of “Generation of vertices” denotes a certain set of vertices with many parents belonging to previous generations. Terminology for this concept, in our opinion, has not yet fully developed. The concept of “Generation” in some cases makes it easier to solve some problems in Bayesian networks and to build simpler algorithms.  In this paper we will consider the well-known example “Asia”, described in many articles and books, as well as in the technical documentation for various toolboxes. For the construction of this example, we have used evaluation versions of AgenaRisk.Niniejszy artykuł koncentruje się na badaniu pewnych aspektów teorii zorientowanych grafów w sieciach bayesowskich. W niektórych artykułach na temat teorii sieci bayesowskich pojęcie „generacji wierzchołków” oznacza pewien zestaw wierzchołków z wieloma rodzicami należącymi do poprzednich generacji. Terminologia tego pojęcia, naszym zdaniem, nie została jeszcze w pełni rozwinięta. Koncepcja „Generacji” w niektórych przypadkach ułatwia rozwiązywanie niektórych problemów w sieciach bayesowskich i budowanie prostszych algorytmów. W tym artykule rozważymy dobrze znany przykład „Azja”, opisany w wielu artykułach i książkach, a także w dokumentacji technicznej różnych zestawów narzędzi. Do budowy tego przykładu wykorzystaliśmy wersje testowe AgenaRisk

Cycles in Bayesian Networks

The article is devoted to some critical problems of using Bayesian networks for solving practical problems, in which graph models contain directed cycles. The strict requirement of the acyclicity of the directed graph representing the Bayesian network does not allow to efficiently solve most of the problems that contain directed cycles. The modern theory of Bayesian networks prohibits the use of directed cycles. The requirement of acyclicity of the graph can significantly simplify the general theory of Bayesian networks, significantly simplify the development of algorithms and their implementation in program code for calculations in Bayesian networks

Clusterization by the K-means method when K is unknown

There are various methods of objects’ clusterization used in different areas of machine learning. Among the vast amount of clusterization methods, the K-means method is one of the most popular. Such a method has as pros as cons. Speaking about the advantages of this method, we can mention the rather high speed of objects clusterization. The main disadvantage is a necessity to know the number of clusters before the experiment. This paper describes the new way and the new method of clusterization, based on the K-means method. The method we suggest is also quite fast in terms of processing speed, however, it does not require the user to know in advance the exact number of clusters to be processed. The user only has to define the range within which the number of clusters is located. Besides, using suggested method there is a possibility to limit the radius of clusters, which would allow finding objects that express the criteria of one cluster in the most distinctive and accurate way, and it would also allow limiting the number of objects in each cluster within the certain range

Economic Clusters as a Form of Self-Organization of the Economic System

The creation of clusters of domestic innovative economy in the Russian Federation is one of the actual directions of intensification of economic and innovative development of the city, region, and country. The importance of this is proved by the fact that when analyzing the direction of development of the country the Government of the Russian Federation has invited Harvard professor Michael Porter, ancestor of the modern theory of competition (Markov, 2007) one of which main provisions is the need for economy clustering as the only independent expert. Nowadays there is the pressing problem and the need for self-organization of the domestic economic system including its regionalization (Larina & Makeev, 2006). Economic clusters are the most theoretically developed and passed experimental test way of self-organization. Economic clusters as structures of self-organization can occur spontaneously or due to induction. In the first case it is the usual process of the economic basis with corresponding criteria of increasing economic feasibility and, in particular, competitiveness. Participation of the Russian Federation in this case comes down to various ways of assistance. The second one is expressed through a system case of organizational innovation. It can be mostly realized with direct interests and spearheaded by the government. Keywords: cluster, system, economy, self-organization, region JEL Classifications: A10, C38, O1