Based On The Data Mining Warehouse Management System Applications And Research

Data Mining (DM) technology is a hot subject in the development of the Warehouse Management System (WMS), which can enable various departments to share data in enterprise-wide, and increase the efficiency of data maintaining, dissemination and query. But the traditional model of the WMS is facing many problems, such as lower response speed and poorer service performance.Therefore,Back Propagation Neural Network (BPNN) DM technology is becoming a hot research in the field of WMS.BPNN DM technology is currently the most efficient mining technology for forecasting the warehouse conditions. DM is the process of mining useful knowledge from a large amount of data which was stored in database, data warehouse, or other information base. Using BPNN DM technology in clothing warehouse management can forecast and analyze the warehouse conditions to reduce the inventory, thus greatly expand the ability of WMS. This paper includes the following research work :(1)The application of improved BP in the system of clothing warehouse management provides high-performance data applications service,enhances the functions of WMS,reduces the stock and effectively controls the ordering.(2)Studies the warehouse technology in warehouse management, proposes a controlling method of clothing warehouse and creates a controlling mould for stage warehouse based on NN.(3)Studies the existing WMS platform, sums up the shortcomings and proposes constructing a system platform by using BPNN technology, SQL technology and Web technology,the application of which proves that the structure of this platform is clear and the efficiency of implementation is high.At the same time, the application technology mentioned in this paper, closely follows the current direction of technology in development and can be used for reference by the research and application of similar topics.