Machine Learning Algorithms with Intermittent Demand Forecasting: An Application in Retail Apparel with Plenty of Predictors

İlker GÜVEN; Özer UYGUN; Fuat ŞİMŞİR

doi:https://doi.org/10.32710/tekstilvekonfeksiyon.809867

Makale detayları

Machine Learning Algorithms with Intermittent Demand Forecasting: An Application in Retail Apparel with Plenty of Predictors

Yazarlar:

İlker GÜVEN | Özer UYGUN | Fuat ŞİMŞİR

Yayıncı:

Ege University

Ana Başlıklar:

Textiles

Dergi:

Textile and Apparel 2021 Vol.31 Issue 2, pp.99-110

Belge Tipi:

Makale

Yayın Tarihi:

6/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000650539

Sıklık:

Üç Aylık

eISSN:

2602-3075

pISSN:

1300-3356

DOI:

https://doi.org/10.32710/tekstilvekonfeksiyon.809867

Özet:

 

Demand forecasting is a key factor for apparel retail stores to sustain their business, especially where there are variety of products and intermittent demand. 
In this study, two of the most popular machine learning methods, random forest (RF) and k-nearest neighbour (KNN), have been used to forecast retail apparel’s intermittent demand. Numerous variables that may have an effect on the sales, have been taken into account one of which is defined as “special day” that might trigger intermittence in the demand. During the application of the forecast, four different datasets were used to provide reliability. 28 different variables were used to increase accuracy of the forecasting and experience of the behaviours of the algorithms. Root mean square error (RMSE) was used to evaluate performance of the methods and as a result of this study, RF showed better performance in all four datasets comparing to KNN.

Makale detayları

Machine Learning Algorithms with Intermittent Demand Forecasting: An Application in Retail Apparel with Plenty of Predictors

Yazarlar: İlker GÜVEN | Özer UYGUN | Fuat ŞİMŞİR

Yayıncı: Ege University

Ana Başlıklar: Textiles

Dergi: Textile and Apparel 2021 Vol.31 Issue 2, pp.99-110

Belge Tipi: Makale

Yayın Tarihi: 6/2021

Belge Dili: İngilizce

Document ID (Org No.): 2000650539

Sıklık: Üç Aylık

eISSN: 2602-3075

pISSN: 1300-3356

DOI: https://doi.org/10.32710/tekstilvekonfeksiyon.809867

Sayı

Yazarlar:

İlker GÜVEN | Özer UYGUN | Fuat ŞİMŞİR

Yayıncı:

Ege University

Ana Başlıklar:

Textiles

Dergi:

Textile and Apparel 2021 Vol.31 Issue 2, pp.99-110

Belge Tipi:

Makale

Yayın Tarihi:

6/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000650539

Sıklık:

Üç Aylık

eISSN:

2602-3075

pISSN:

1300-3356

DOI:

https://doi.org/10.32710/tekstilvekonfeksiyon.809867