Development of regression coefficient selection quality criterion in power consumption forecasting problems - Тимчук, Сергей Александрович; Катюха, Игорь Анатольевич (Eastern-European Journal of Enterprise Technologies, 2014)
Forecasting electricity consumption is necessary for industrial enterprises since it allows to optimize its development strategy. The initial information uncertainty problem, arising thereat is also solved using fuzzy regression analysis. Herewith, most authors estimate the quality of determining regression coefficients according to one of the criteria: maximum compatibility of data and model or minimum fuzziness of the model. These criteria are contradictory and using only one of them affects the forecasting quality. To justify the developed quality assessment criterion of the forecast model, its unambiguous relationship with traditionally used forecast quality assessment based on the relative mean module error by modal values was mathematically proved. To solve the problem of searching fuzzy regression coefficients using the developed criterion, a simple algorithm that implements the ideas of the method of spatial variable-pitch grid was proposed. The choice of method is caused by the fact that the possible nonlinearity of the regression forecast model requires the global optimum search method. Absolute convergence of the method is also very important. In general, the results obtained allow to improve informativeness of system for forecasting power consumption of enterprise under initial information uncertainty.