Research On The Application Of Data Mining In The Logistics Warehouse Management System

With the continually improving degree of logistics information, logistics warehouse management system has been widely applied in the logistics business. As a part which is the joint of all aspects of the logistics, WMS randomly generated a large amount of business data in storage management, stock-out management, in-library management, commodity inventory and other business. There is a lot of useful and valuable information hidden in this large amount of data, but the lack of comprehensive analysis and applications of these data makes it difficult for clients to use it directly. However, we can obtain the knowledge required from a lot of data and information in stock-out by data mining.This topic focuses on the problem of large amounts of data in the Hongyun logistics warehouse management system which can not be directly used by the clients to provide useful and valuable information; puts forward the idea of mining the data in the Association Rules from a large amount of data information in stock-out by using related data mining technologies; and then makes reasonable arrangements on the storage spaces to improve warehouse efficiency.Based on a series of processing and conversion on the stock-out information in the logistics warehouse management system to form the target database, which will be converted to DAT files through the java code; and based on the java program developed by FP-growth algorithm to deal with and construct data in the DAT files to output a corresponding set of frequency, FP tree, pattern conditions, conditions of FP tree and frequency pattern list of other objects and then successfully excavate the relationship among commodity groups and form the frequency pattern, this paper comes to the strategy of how enterprises should arrange storage spaces for the goods.