Abstract
Cross-border e-commerce logistics cost prediction algorithm does not consider logistics distribution scheduling, and logistics information interchange is not enough, which leads to confusion of logistics cost parameters and large deviation. Therefore, an intelligent prediction algorithm of cross-border e-commerce logistics cost based on cloud computing is designed. Introduce cloud computing platforms, optimize the scheduling of cross-border e-commerce logistics distribution tasks, and select the targets for the scheduling of cross-border e-commerce logistics distribution tasks from the aspects such as the shortest waiting time required by customers, the degree of resource load balance, and the costs consumed in completing cross-border e-commerce logistics distribution tasks, and design logistics scheduling process. On this basis, the logistics distribution data are classified, the association rules between the data are mined, and the monitoring of abnormal values in the cost forecasting process is completed. In order to eliminate the interference caused by the difference of different cost management interval, the function value is calculated by weighted Euclidean distance. Design feedback forecast mechanism to realize intelligent forecast algorithm of cross-border e-commerce logistics cost. Experimental results show that the proposed algorithm has better accuracy of cross-border e-commerce logistics cost prediction and higher completion rate of logistics tasks.
Highlights
In order to optimize the research on cross-border e-commerce logistics costs, some good results have been achieved
The above two methods ignore the consideration of logistics distribution scheduling, and the amount of logistics information interaction is not enough, resulting in confusion of logistics cost parameters and large errors in cost prediction. erefore, an intelligent prediction algorithm of cross-border e-commerce logistics cost based on cloud computing is designed
(2) rough the introduction of cloud computing platform, we optimize the scheduling of cross-border e-commerce logistics and distribution tasks and design the logistics scheduling process from the minimum waiting time required by customers, the load balancing degree of resources, and the cost consumed in completing cross-border e-commerce logistics and distribution tasks
Summary
Economics and Management School, Jilin Agricultural Science and Technology University, Jilin 132101, China. (2) rough the introduction of cloud computing platform, we optimize the scheduling of cross-border e-commerce logistics and distribution tasks and design the logistics scheduling process from the minimum waiting time required by customers, the load balancing degree of resources, and the cost consumed in completing cross-border e-commerce logistics and distribution tasks. Using the shortest waiting time target needed for the customer, the time spent in processing the cross-border e-commerce logistics distribution task is calculated, and the calculation of resource load balance degree and the cost for completing the multiobjective logistics distribution task is combined to establish a mathematical model to measure the scheduling effect of the multiobjective logistics distribution task, and the target of the scheduling of multiobjective logistics distribution task in cloud computing is selected [14]. A new cost forecasting method is studied. is method uses cluster analysis, classification analysis, anomaly analysis, cluster analysis, and
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