Application Research of Data Mining in Urban Logistics Planning

Author:

Wang Xiaohu1ORCID

Affiliation:

1. Intelligent Manufacturing College, Tianjin Sino-German University of Applied Sciences, Tianjin 300350, China

Abstract

With the continuous development of information technology and the arrival of the era of big data, data mining technology has been applied in more and more fields. Data mining refers to the process of searching for information hidden in a large amount of data through algorithms. This process uses various technical methods and has a wide range of applications. Urban logistics is a special logistics system, an open and complex system, which has a profound impact on the development of cities. Using data mining technology to plan urban logistics can more efficiently improve the speed of urban logistics, save logistics costs, and speed up the construction of urban economy. This paper is aimed at studying urban logistics planning model based on data mining and analyzing the calculation accuracy and reliability of the model. This paper proposes to establish a relevant input-output data mining model according to the relationship between various industries and logistics in the city and conduct a calculation test on the model. The test results show that the data mining model proposed in this paper has an average calculation accuracy of over 85% and a maximum of 99%, which shows that the model has strong practical reliability and can be effectively applied to the planning of urban logistics.

Funder

Tianjin Municipal Science and Technology Bureau

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Guidelines for Inventory Cost Reduction in Finished Goods for Competitive Advantage;WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS;2023-09-15

2. Retracted: Application Research of Data Mining in Urban Logistics Planning;Wireless Communications and Mobile Computing;2023-07-19

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