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This paper proposes a model that uses a deep neural network to predict backorders; it handles the data imbalance between backorders and filled orders with ...
This paper proposes a model that uses a deep neural network to predict backorders; it handles the data imbalance between backorders and filled orders with ...
Oct 22, 2024 · This paper proposes a model that uses a deep neural network to predict backorders; it handles the data imbalance between backorders and filled orders with ...
A model that uses a deep neural network to predict backorders; it handles the data imbalance between backorders and filled orders with efficient techniques ...
The predictive model learns the likelihood of product backorders by using the training samples. We conduct experiments on a large benchmark dataset to test the ...
Jul 4, 2024 · This paper proposes a model that uses a deep neural network to predict backorders; it handles the data imbalance between backorders and filled ...
Oct 25, 2023 · Our proposed model demonstrates remarkable accuracy in predicting backorders on short and imbalanced datasets. We capture intricate patterns and ...
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Nov 9, 2022 · We propose a new convolutional neural network (CNN)-based explainable predictive model for product backorder prediction in inventory management.
The objective is to use predictive analytics and machine learning to reliably estimate future backorder risk and then discover the best method for inventorying ...
Customer backorder prediction in the supply chain involves developing algorithms using historical data to forecast the probability of a product going out of ...