Forecasting product sales amounts by artificialneural network: An application in the furnitureindustry
2022
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Advisor: Doç. Dr. Alparslan Serhat Demir
Abstract (EN)
In order for businesses to respond to customer demands in the right time and amount, they need to give importance to demand forecasting studies. Predicting how much of each product should be produced with high accuracy will increase customer satisfaction and help businesses gain a better place in the market and ensure their continuity. In this study, a demand forecasting application was made in a company operating in the furniture industry with Artificial Neural Networks (ANN), which is one of the frequently used artificial intelligence techniques. ABC analysis was performed in the company, and sales forecasts were made for bed and sofa mechanisms, which are among the most consumed components by value. As the input factors affecting the sales amount of the mechanism; It has been determined that the furniture industry industrial production index, dollar rate and price change criteria affect the sales amount. With the network created in the Matlab Program, the sales amounts for the next year were estimated. The obtained results show that the ANN technique can obtain highly accurate predictions.
Author
Dr. Burçin Salttürk
Institution
How to Cite
Burçin Salttürk (Master Thesis). Forecasting product sales amounts by artificialneural network: An application in the furnitureindustry, 2022, Sakarya University.
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