Design And Implementation Of Railway Container Freight Marketing Data Analysis System

At present,China’s transportation industry is developing rapidly.The freight industry is no longer dominated by railways,but has formed a diversified development pattern of railways,water transportation,highways and aviation.Railway container transportation enterprises are facing huge challenges.In order to improve the quality of railway freight services and improve the level of railway freight operations,railway container transport companies need to carry out freight marketing,strengthen freight marketing effects,change operational concepts in a timely manner,pay attention to customer relationship management,formulate personalized marketing strategies,and establish railways that adapt to the contemporary market.Container freight marketing system.On the basis of demand analysis,a system design scheme with customer relationship management as the core,transportation price adjustment as a strategy,and data visualization as an auxiliary is proposed to obtain the overall system structure,database and functional module design results.Based on the MVC framework,using Java Web technology and My SQL database to build a Tomcat server to complete the design and development of the railway container freight marketing data analysis system.From the perspective of system design,the main research contents of this thesis are as follows:(1)Customer relationship management.Processing redundant railway container freight customer information,integrating customer resources,proposing a customer value-based railway container freight customer segmentation model,and combining isolated forest and k-means clustering algorithm to classify railway container freight customers.(2)Transportation price adjustment.The freight market is subdivided into an agreement market and a free market,and with the goal of maximizing the operating income of railway transportation companies,the optimization model of railway container empty and heavy container transportation and pricing is established,and the particle swarm algorithm is applied to solve the problem.The feasibility of the model is proved through the analysis of examples.(3)Data visualization module.According to the results of data collection,customer information collation and project price adjustment,various business data are statistically analyzed from multiple angles and dimensions to assist business personnel in in-depth analysis of changes in customer behavior and freight production,and solve the difficulties of marketing dynamic analysis.