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Multiple criteria inventory classification based on principal components analysis and neural network. (English) Zbl 1084.68662

Wang, Jun (ed.) et al., Advances in neural networks – ISNN 2005. Second international symposium on neural networks, Chongqing, China, May 30 – June 1, 2005. Proceedings, Part III. Berlin: Springer (ISBN 3-540-25914-7/pbk). Lecture Notes in Computer Science 3498, 1058-1063 (2005).
Summary: The paper presents two methods for ABC classification of stock keeping units (SKUs), The first method is to apply principal components analysis (PCA) to classify inventory. The second method combines PCA with artificial neural networks (ANNs) with BP algorithm. The reliability of the models is tested by comparing their classification ability with a data set. The results show that the hybrid method could not only overcome the shortcomings of input limitation in ANNs, but also further improve the prediction accuracy.
For the entire collection see [Zbl 1073.68015].

MSC:

68T05 Learning and adaptive systems in artificial intelligence
92B20 Neural networks for/in biological studies, artificial life and related topics
90B05 Inventory, storage, reservoirs
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