Material demand forecasting with classical and fuzzy time series models

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15210%2F21%3A73612049" target="_blank" >RIV/61989592:15210/21:73612049 - isvavai.cz</a>
Result on the web
<a href="https://annals-csis.org/Volume_29/drp/pdf/8.pdf" target="_blank" >https://annals-csis.org/Volume_29/drp/pdf/8.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.15439/2021B8" target="_blank" >10.15439/2021B8</a>

Result language
angličtina
Original language name
Material demand forecasting with classical and fuzzy time series models
Original language description
Direct material budgeting is an essential part of financial planning processes. It often implies the need to predict quantities and prices of hundreds of thousands of materials to be purchased by an enterprise in the upcoming fiscal period. Distortion effects in demand projections and overall uncertainty cause the enterprises to rely on internal data to build their forecasts. In this paper we are dealing with material demand forecasting and evaluate the feasibility of fuzzy time series forecasting models as compared to classical forecasting models. Relevant methods are shortlisted based on existing practice described in academic research. Three datasets from industry are used to evaluate the predictive performance of the shortlisted methods. Our findings show an improvement in prediction accuracy of up to 47% compared to naïve approach. Fuzzy time series models are reported to be the most reliable forecasting method for the analyzed intermittent time series in all three datasets.
Czech name
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Czech description
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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