2023
DOI: 10.1109/access.2023.3333030
|View full text |Cite
|
Sign up to set email alerts
|

Outlier-Aware Demand Prediction Using Recurrent Neural Network-Based Models and Statistical Approach

Yuseon Kim,
Kyongseok Park

Abstract: The paint industry comprises an elaborate supply chain involving various activities such as raw material procurement, manufacturing, and distribution. In addition, the accuracy of demand prediction significantly impacts supply chain management. A recurrent neural network (RNN) is a powerful method that learns intricate patterns through vast amounts of historical data and provides a prediction, demonstrating excellent performance in demand prediction. However, standard RNN-based demand predictions are limited b… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 40 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?