Inventory forecasting based on artificial intelligence
Subject Areas : ManagementHamidreza Hadjali 1 , Mohammad Ali Afshar Kazemi 2 , Adel Azar 3 , Abbas Toloie Eshlaghy 4 , Reza Radfar 5
1 - Management; Faculty of Industrial Management; Science and Research Branch, Islamic Azad University;Tehran;Iran
2 - Islamic Azad University
3 - Tarbiat modares university
4 - Faculty of Management, Science and Research Branch, Islamic Azad University
5 - Management; Faculty of Industrial Management; Science and Research Branch, Islamic Azad University;Tehran;Iran
Keywords: Inventory control, big data, artificial intelligence, deep learning, supply chain,
Abstract :
Development of artificial intelligence in broad industrial and commercial fields, and significant increasing of non-linear data which produced by various units of organizations, on the other hand, would be necessary for using artificial intelligence (IA) in inventory management (IM).That's why the strategic model recommended in this article aims to use deep learning methods of long-term memory (RNN) and bidirectional long-term short-term memory (BILSTM) neural network based on regular inventory control methods such as the economic value of the order( EOQ) and the economic production quantity model (EPQ) also use of ABC analysis which facilities would increase effectiveness of model. The achievement of this article is reach a unique strategic model, by integration of traditional inventory control methods and artificial intelligence, which has high efficiency in terms of speed and accuracy of forecasting. However the findings have been showed that the recurrent neural network(RNN) with an accuracy of 85% did not acceptable and combined approach of the (BILSTM) neural network, after building and training by considered parameters in line with the purpose of the article, has explained the accuracy of 93%.
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