Warehouse Automation Replenishment Warning Method Based on Big Data and Convolutional Neural Networks
Warehouse warning is an important part of warehouse automation management and also the core function of automation management systems. However,the current warning methods have been unable to achieve the expected warning effect due to low warning accuracy,which has led to delays and backlogs in warehouse orders. Therefore,a warehouse automation replenishment warning method based on big data and convolutional neural networks is proposed. Firstly,the warehouse replenishment data is automatically collected using a combination of electronic tags and readers,and the Find function in big data technology is used as a data cleaning tool to clean the raw data,achieving the integration of warehouse automation replenishment big data. Then,convolutional neural network technology is used to analyze big data and extract warehouse replenishment features. Finally,a comprehensive analysis method is used to evaluate the level of warehouse replenishment warning,achieving automated warehouse replenishment warning based on big data and convolutional neural networks. Experimental results have shown that the application of design methods effectively reduces the number of delayed warehouse orders and inventory backlog,enabling precise warning of automated replenishment in the warehouse.
big dataconvolutional neural networkwarehouseautomated replenishmentFind functioncomprehensive analysis method
万方数据
维普
