Sale Prediction in Textile Industry with Hybrid Deep Learning Using Time Series Images
A deep learning model was developed to predict sales in the textile industry using time series images.
Researchers created a model that converts sales data into images and uses convolutional neural networks to classify them. This method aims to improve sales forecasting in the textile industry, which is a significant contributor to Turkey's exports. The study's goal is to help companies make more accurate future plans.
Abstract
In 2021, exports of 12.9 billion dollars in the field of textiles in Turkey's exports have an important place in all export income. In the reports published on the textile industry, this figure is expected to increase even more in the coming years. As in other sectors, accurate estimation of sales revenues in the textile sector is very important for the future plans of companies. In this study, a deep learning model has been developed for demand and sales forecasting in the textile industry. In the method used, income will be converted to image data with Gramm Angular Fields of time series. Convolutional neural networks were used to classify these images.
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Balcı, M. A., Akgüller, Ö., Ayakta, D. Y., İldeniz, A. (2022). Sale Prediction in Textile Industry with Hybrid Deep Learning Using Time Series Images. *The European Journal of Research and Development*, 2(2), 301 - 314. https://doi.org/10.56038/ejrnd.v2i2.67
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