DERİN SİNİR AĞLARI KULLANARAK TÜRKİYE’DEKİ OTOMOBİL SATIŞLARININ TAHMİNİ İÇİN BİR MODEL

Year 2020, Volume: 31 Issue: 1, 57 - 74, 30.04.2020

Sema Kayapınar Kaya , Özal Yıldırım

Abstract

Özet: Tüm kararlarda itici güç olan tedarik zinciri sürecinde talep tahmini, tedarik zinciri sürecinin en önemli bileşenlerinden birisidir. Gelecekteki ürün ve hizmetlerin tahmin edilmesi, diğer tüm tahminlerin başlangıç noktası olup diğer tüm süreçlerin temel girdisini oluşturmaktadır. Bu çalışmada, otomobil satış tahmini için 8 katmanlı Derin Sinir Ağ modeli önerilmiştir. Modelin girdileri, Döviz Kuru, Gayrisafi Yurt içi Hasıla, Tüketici Güven Endeksi ve Tüketici Fiyat Endeksi gibi faktörlerden oluşmaktadır. Modelin çıkışına göre araç satış tahmini yapılmıştır. 2011 ve 2018 yılları arasında aylık bazda toplam 90 veri toplanılarak analizler yapılmıştır.

Keywords

Derin Sinir Ağı, Tedarik Zinciri Yönetimi, Satış tahmini

Supporting Institution

yok

Project Number

yok

A PREDICTION MODEL FOR AUTOMOBILE SALES IN TURKEY USING DEEP NEURAL NETWORKS

Abstract

Demand prediction in the supply chain process, which is the driving force in all decisions, is one of the most important components of the supply chain process. Prediction of future goods and services is the starting point of all other predictions and provides the basic entry to all other functions. In this study, an 8-layer Deep Neural Network model was recommended for vehicle sales prediction. The inputs of the model consist of features, such as exchange rate, the gross domestic product, consumer confidence index, and the consumer price index. The vehicle sales forecast was made according to the output of the model. We analyzed a total of 90 data on a monthly basis between the years of 2011 and 2018 was collected.

Keywords

Deep Neural Network, Supply Chain Management

Project Number

yok

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