An Inventory Controlled Supply Chain Model Based on Improved BP Neural Network
Inventory control is a key factor for reducing supply chain cost and increasing customer satisfaction. However, prediction of inventory level is a challenging task for managers. As one of the widely used techniques for inventory control, standard BP neural network has such problems as low convergenc...
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2013/537675 |
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| _version_ | 1832562452735197184 |
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| author | Wei He |
| author_facet | Wei He |
| author_sort | Wei He |
| collection | DOAJ |
| description | Inventory control is a key factor for reducing supply chain cost and increasing customer satisfaction. However, prediction of inventory level is a challenging task for managers. As one of the widely used techniques for inventory control, standard BP neural network has such problems as low convergence rate and poor prediction accuracy. Aiming at these problems, a new fast convergent BP neural network model for predicting inventory level is developed in this paper. By adding an error offset, this paper deduces the new chain propagation rule and the new weight formula. This paper also applies the improved BP neural network model to predict the inventory level of an automotive parts company. The results show that the improved algorithm not only significantly exceeds the standard algorithm but also outperforms some other improved BP algorithms both on convergence rate and prediction accuracy. |
| format | Article |
| id | doaj-art-2575781d282d4b2ab1d85d6670526e30 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-2575781d282d4b2ab1d85d6670526e302025-02-03T01:22:29ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2013-01-01201310.1155/2013/537675537675An Inventory Controlled Supply Chain Model Based on Improved BP Neural NetworkWei He0Research Center of Cluster and Enterprise Development, School of Business Administration, Jiangxi University of Finance & Economics, Nanchang 330013, ChinaInventory control is a key factor for reducing supply chain cost and increasing customer satisfaction. However, prediction of inventory level is a challenging task for managers. As one of the widely used techniques for inventory control, standard BP neural network has such problems as low convergence rate and poor prediction accuracy. Aiming at these problems, a new fast convergent BP neural network model for predicting inventory level is developed in this paper. By adding an error offset, this paper deduces the new chain propagation rule and the new weight formula. This paper also applies the improved BP neural network model to predict the inventory level of an automotive parts company. The results show that the improved algorithm not only significantly exceeds the standard algorithm but also outperforms some other improved BP algorithms both on convergence rate and prediction accuracy.http://dx.doi.org/10.1155/2013/537675 |
| spellingShingle | Wei He An Inventory Controlled Supply Chain Model Based on Improved BP Neural Network Discrete Dynamics in Nature and Society |
| title | An Inventory Controlled Supply Chain Model Based on Improved BP Neural Network |
| title_full | An Inventory Controlled Supply Chain Model Based on Improved BP Neural Network |
| title_fullStr | An Inventory Controlled Supply Chain Model Based on Improved BP Neural Network |
| title_full_unstemmed | An Inventory Controlled Supply Chain Model Based on Improved BP Neural Network |
| title_short | An Inventory Controlled Supply Chain Model Based on Improved BP Neural Network |
| title_sort | inventory controlled supply chain model based on improved bp neural network |
| url | http://dx.doi.org/10.1155/2013/537675 |
| work_keys_str_mv | AT weihe aninventorycontrolledsupplychainmodelbasedonimprovedbpneuralnetwork AT weihe inventorycontrolledsupplychainmodelbasedonimprovedbpneuralnetwork |