Issues of Improving the Accuracy of Demand and Sales Forecasting Using Decomposition of Components and Fuzzy Error Estimation

DOI

10.2991/csit-19.2019.33How to use a DOI?

Keywords

planning, forecast, regression, deviations, fuzzy number, time series decomposition, decision making support.

Abstract

The efficiency of production and sales systems focused on public markets and the enlargement of variable parts of the orders depends on the accuracy of demand and forecasting and planning of production volumes. To tackle the problem of improving the forecasting accuracy of time series in this paper we have tested the hypothesis that the parameters associated with the flow of orders contain several components that can be described separately using existing approaches. Hence, the forecasting error can be represented as a set of fuzzy numbers. Hence, the forecasting error can be represented as a set of time series' fuzzy numbers. As a result of the hypothesis investigation, we obtained forecasting data in its fuzzy form, which already contains results of possible deviations and their probability. Moreover, this method of using fuzzy numbers may improve the accuracy of forecasting. The use of fuzzy forecasts allows us to solve planning and management problems in its fuzzy formulation and thereby to obtain results containing assessments of the range of possible deviations, risks and possible strategies of behaviour without additional research.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Leonid Mylnikov
AU  - Dmitrii Vershinin
AU  - Artur Mikhailov
PY  - 2019/12
DA  - 2019/12
TI  - Issues of Improving the Accuracy of Demand and Sales Forecasting Using Decomposition of Components and Fuzzy Error Estimation
BT  - Proceedings of the 21st International Workshop on Computer Science and Information Technologies (CSIT 2019)
PB  - Atlantis Press
SP  - 191
EP  - 195
SN  - 2589-4900
UR  - https://doi.org/10.2991/csit-19.2019.33
DO  - 10.2991/csit-19.2019.33
ID  - Mylnikov2019/12
ER  -