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About Application of Data Mining For Supply Chain Inventory Forecasting
This document discusses using data mining techniques to improve inventory forecasting for supply chain management. It describes clustering stores based on sales patterns and then using decision trees and neural networks on the store clusters to more accurately predict out-of-stock events at the store/product level. The methodology is applied to inventory management in an automotive supply chain, extracting data from various sources into a data warehouse to power the forecasting models.
Detailed Information
| Author: | ['Willem Warella'] |
|---|---|
| Publication Year: | 2012 |
| Pages: | 14 |
| Language: | English |
| Format: | |
| Price: | FREE |
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