Evaluation of the financial condition of the enterprise in the field of services with the use of Kochonen's maps

Abstract

The article is devoted to the research of financial condition of the enterprise sphere of services. Stabilization of the financial state is a priority direction of a separate enterprise and the economic system as a whole.

In the article the resolve to ensure stability of financial activity using a neural network model clustering - Kohonen self-organizing maps powerful clustering mechanism that allows you to display the results of the financial analysis in a compact and easy to interpret two-dimensional maps.

Managing enterprise financial stability organic part of the system of income and expenditure, the movement of assets, capital and cash flow management of its capital structure and other aspects of its operations Kohonen's maps are designed for visual representation of multidimensional properties of objects on a plane with two axes. Maps of Kohonen carry the display of high-dimensional input data on elements of a regular array of small dimensions (usually two-dimensional). Maps of Kohonen are similar to Kohonen's network. The difference between the maps and the networks of Kohonen is that in the map of the neurons, which are the centers of the clusters, they are arranged in a certain structure (usually a two-dimensional grid). As a result, some close to the sensor input vector network Kohonen belong to one neuron (cluster center), and Kohonen's maps can relate to different closely spaced on a grid of neurons. Typically, neurons are located in nodes of a two-dimensional mesh with rectangular or hexagonal cells.

This paper analyzes the service company and hold segmentation framework visitors built profiles of service users by identifying their similar behavior in terms of frequency, type of ordered services and evaluated the most and least profitable segments.

Segmentation of hotel-restaurant visitors was carried out using an approach based on the Kohonen algorithm and a clustering of objects by Kohonen algorithm.

This interface is used to look for regularities in large data arrays. This allows for a reconnaissance analysis of data that is different from the classical statistical procedures.

The investigated approach of grouping services is different, because it takes into account not only a separate generalized level of financial stability, but also the entire structural characteristics of the enterprise and its specialization. The services provided by an enterprise can be grouped into specific groups, depending on their place in the system of enterprise activity, they are grouped according to certain indicators involved in clusterization.