International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 175 - Issue 22 |
Published: Oct 2020 |
Authors: Aturika Bhatnagar, Rajeev Gupta, G.D. Thakar |
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Aturika Bhatnagar, Rajeev Gupta, G.D. Thakar . Prediction of Demand for Supply Chain using Time Series Predictive Models. International Journal of Computer Applications. 175, 22 (Oct 2020), 33-39. DOI=10.5120/ijca2020920744
@article{ 10.5120/ijca2020920744, author = { Aturika Bhatnagar,Rajeev Gupta,G.D. Thakar }, title = { Prediction of Demand for Supply Chain using Time Series Predictive Models }, journal = { International Journal of Computer Applications }, year = { 2020 }, volume = { 175 }, number = { 22 }, pages = { 33-39 }, doi = { 10.5120/ijca2020920744 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2020 %A Aturika Bhatnagar %A Rajeev Gupta %A G.D. Thakar %T Prediction of Demand for Supply Chain using Time Series Predictive Models%T %J International Journal of Computer Applications %V 175 %N 22 %P 33-39 %R 10.5120/ijca2020920744 %I Foundation of Computer Science (FCS), NY, USA
Accuracy in the prediction of demand is an important task in any field of business. Prediction of the expected sales ensures the smooth working of an organization as well as helps in maintaining the balance all around the company. For a pump manufacturing company predicting demand can be a tedious task due to the involvement of the multiple factor environmental conditions. In this context, this paper focuses on the prediction of the demand using Holt Winter's model and ARIMA model and then validating their accuracy by MAPE and Theil's-U.