Dynamic Data Mining Method of Cold Chain Logistics in Drug Distribution Under the Background of Cloud Computing

Because of the huge volume of cold chain logistics data, the traditional data dynamic mining method can not mine the whole local drug circulation data, resulting in the lack of a large number of data mining results, reducing the integrity of the data. Therefore, in the context of cloud computing, a new dynamic mining method is proposed for the cold chain logistics data of drug circulation. Under the cold chain logistics model, the method is further developed by defining the drug circulation mode. The data mining uses cloud computing technology to extract the target data; uses data cleaning, data elimination, data supplement and data conversion to preprocess the target data; according to the association rules between the acquired data, realizes the dynamic mining of cold chain logistics data information. Experiments show that, compared with the traditional methods, the proposed mining method can find the target data in the huge cold chain logistics data, and achieve all the data mining. It can be seen that the data mining method proposed in this paper has higher data integrity.