Method for Automatic Analysis of Compliance of Expenses Data and the Enterprise Income by Neural Network Model of Forecast

Abstract

The problem of automation of audit data analysis the prerequisite "Compliance of costs and incomes" based on the forecast is considered. A neural network model for forecast based on a gateway recurrent unit is proposed. For parametric identification of this model, adaptive cross entropy is proposed. This allows you to increase the forecast efficiency by reducing computational complexity and improving the forecast accuracy. Software was developed using the Matlab package that implements the proposed method. The developed software is studied when solving the problem of forecasting indicators in the task of analyzing the data mapping “settlements with suppliers - settlements with customers”.