Order Demand Forecast Using a Combined Approach of Stepwise Linear Regression Coefficients and Artificial Neural Network

Serdar GÜNDOĞDU

doi:https://doi.org/10.17798/bitlisfen.1059772

Makale detayları

Order Demand Forecast Using a Combined Approach of Stepwise Linear Regression Coefficients and Artificial Neural Network

Yazarlar:

Serdar GÜNDOĞDU

Yayıncı:

Bitlis Eren University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Bitlis Eren Üniversitesi Fen Bilimleri Dergisi 2022 Vol.11 Issue 2, pp.564-573

Belge Tipi:

Makale

Yayın Tarihi:

6/2022

Belge Dili:

İngilizce

Document ID (Org No.):

2000888235

Sıklık:

Üç Aylık

eISSN:

2147-3188

pISSN:

2147-3129

DOI:

https://doi.org/10.17798/bitlisfen.1059772

Özet:

 

Abstract
Nowadays, businesses' forecasts to meet the demands have become more critical. This study aimed to predict the fifteen-day order demand for an order fulfillment center using a Multilayer Perceptron Neural Network (MLPNN). The dataset used in the study was created from a real database of a large Brazilian logistics company and thirteen variables. Linear Regression Coefficients (LRC) were used as a feature selection method to reduce estimation errors. The study showed that among the variables, order type_A (A5), order type_B (A6), and order type_C (A7) had the most significant impact on total order forecasting. The effect of A6 was found to be greater than the effect of A7 and A5. The performance of the proposed model was evaluated using the mean absolute percent error (MAPE). LRC-MLPNN provided a MAPE of 2.97%. The results showed that better forecasting performance was obtained by selecting the independent variables to be used as input to the forecasting model with LRC. The proposed model can also be applied to different estimation problems.

Makale detayları

Order Demand Forecast Using a Combined Approach of Stepwise Linear Regression Coefficients and Artificial Neural Network

Yazarlar: Serdar GÜNDOĞDU

Yayıncı: Bitlis Eren University

Ana Başlıklar: Uygulamalı fizik

Dergi: Bitlis Eren Üniversitesi Fen Bilimleri Dergisi 2022 Vol.11 Issue 2, pp.564-573

Belge Tipi: Makale

Yayın Tarihi: 6/2022

Belge Dili: İngilizce

Document ID (Org No.): 2000888235

Sıklık: Üç Aylık

eISSN: 2147-3188

pISSN: 2147-3129

DOI: https://doi.org/10.17798/bitlisfen.1059772

Sayı

Yazarlar:

Serdar GÜNDOĞDU

Yayıncı:

Bitlis Eren University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Bitlis Eren Üniversitesi Fen Bilimleri Dergisi 2022 Vol.11 Issue 2, pp.564-573

Belge Tipi:

Makale

Yayın Tarihi:

6/2022

Belge Dili:

İngilizce

Document ID (Org No.):

2000888235

Sıklık:

Üç Aylık

eISSN:

2147-3188

pISSN:

2147-3129

DOI:

https://doi.org/10.17798/bitlisfen.1059772