Current State and Diagnostics of the Consumer Goods Market Using Neural Networks

Rena M.

14th International Conference on Applications of Fuzzy Systems, Soft Computing, and Artificial Intelligence Tools, ICAFS 2020, Budva, Montenegro, 27 - 28 August 2020, vol.1306, pp.337-345 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 1306
  • Doi Number: 10.1007/978-3-030-64058-3_42
  • City: Budva
  • Country: Montenegro
  • Page Numbers: pp.337-345
  • Keywords: Consumer goods market, Forecasting methods, Neural networks, Neural networks with a time lag, The volume of retail turnover
  • Azerbaijan State University of Economics (UNEC) Affiliated: Yes

Abstract

This work is devoted to the study of the possibilities of using neural networks to solve the problem of predicting the volume of retail turnover of the consumer goods market per capita in order to determine the further level of development of the population’s security. The difficult point in forecasting the retail turnover of the consumer goods market is the choice of forecasting methods that differ from other commodity markets. The solutions to the problem posed using methods for forecasting time series using the Neural Network Toolbox package of the MATLAB system are considered.