Affiliation:
1. Economics and Management School, Jilin Agricultural Science and Technology University, Jilin 132101, China
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.
Funder
Rural Revitalization Research Base Project of Jilin Branch of Jilin Academy of Social Sciences
Subject
Computer Science Applications,Software
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