USING MODELS SYNTHESIZED BY GMDH MULTI-SELECTION ALGORITHM FOR FORECASTING PROFIT OF JSC “KHMELNYTSKY REGIONAL BREWERY”
Journal Title: Проблеми системного підходу в економіці - Year 2018, Vol 1, Issue 63
Abstract
Prediction stands strong basis for creating the foundations for a successful business and management activities. It takes place in order to promote the development of any organization and production system and is carried out in a variety of conditions – from predominantly deterministic to indefinite, with the domination of randomness. Prediction, in order to increase the efficiency of the decision-making process, is an important part of the activity of the management bodies of economic entities. Using reliable financial forecasts, you can get an idea about the potentials of the company, predict the appropriate ways of its development, substantiate rational management decisions. In the exploration, we have worked out financial statements and profit dynamics of JSC “Khmelnytsky Regional Brewery”, which selected a number of costs of the company, which we consider factors that have an impact on the resultant variable. As a result of a program implementation of the algorithm multi-selection of the method of group consideration of arguments, we received five models. The greatest number of arguments that could be taken into account in the mathematical modelling in economics is three. We analysed the mean square and absolute deviations of the models, and the magnitude of the relative error of the simulation, and according to the given data, a model is selected that is the most accurate among the rest. To determine the impact of various arguments for profit, we decided to increment each of the arguments taken into account in the model by 10% in turn. The obtained results indicate the highest dependency of the profit of JSC “Khmelnitsky Regional Brewery” on the volume of sales products – it changes, and the resultant effect is growing the most. Based on this fact, it is right to suggest the enterprise to pay attention to the potential for increasing sales in the overall increase in profit. The simulation results are not in conflict with economic theory and comply with existing ideas. Taking into account the accuracy of modelling and the correspondence of trend patterns, synthesized models can be proposed for use as predictive in the study of food industry enterprises, in particular, beer factories.
Authors and Affiliations
V. Yu. Rud, V. G. Shchuka
Keywords
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