Research on Regional Logistics Integration of Wuhan City Circle under the Background of Big Data
Yu Zhao
Abstract
Open-access reader
Yu Zhao
Abstract
Open-access reader
Wuhan city circle refers to the city circle which is made up of various prefecture cities with the radius of 100 kilometers around the center of Wuhan.The establishment of efficient Wuhan city circle regional logistics integration system can promote the coordinated development of the urban circle, and adjust the industrial structure, and reduce the logistics costs.In Wuhan city circle the e-commerce rises rapidly in this internet era, the big data technology for Wuhan city circle regional logistics integration system construction, development and innovation has very important application value.Relying on the use of big data technology optimizes Wuhan city circle regional logistics integration of cyber source configuration, and forms Wuhan city circle mutual integration, reduces costs effectively and improves logistics efficiency, realizes the target of regional logistics integration in Wuhan city circle.
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Wuhan city circle refers to the city circle which is made up of various prefecture cities with the radius of 100 kilometers around the center of Wuhan.The establishment of efficient Wuhan city circle regional logistics integration system can promote the coordinated development of the urban circle, and adjust the industrial structure, and reduce the logistics costs.In Wuhan city circle the e-commerce rises rapidly in this internet era, the big data technology for Wuhan city circle regional logistics integration system construction, development and innovation has very important application value.Relying on the use of big data technology optimizes Wuhan city circle regional logistics integration of cyber source configuration, and forms Wuhan city circle mutual integration, reduces costs effectively and improves logistics efficiency, realizes the target of regional logistics integration in Wuhan city circle.
Key concepts: Big data, Computer science, Business, Data science, Data mining