Multiple Criteria Inventory Classification Based on Principal Components Analysis and Neural Network

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.

Abstract

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.