Research on highway freight pricing based on machine learning

The logistics industry has become an important support for China's economy, and the road freight transportation business is the mainstay of the domestic logistics market. The highway network has created good conditions for highway freight transportation. With its advantages of flexibility and adaptability, highway transportation has assumed most of the transportation tasks in the domestic freight market and occupied most of the domestic freight market. At present, there are a large number of individual transporters in the road freight market, and there are problems such as oversupply of services and low freight rates. With the increase in transportation costs, the profit margin is getting smaller and smaller. What's more, there is still malicious price competition in the road freight market, which leads to the confusion of freight prices in the road freight market. Based on this, this paper extracts the factors and characteristics that affect the price of highway vehicle transportation, applies the tree model to train after correlation analysis, and Stacks the adjusted model. The results show that the average quotation deviation rate of the model after Stacking fusion is small and the effect is good, which provides an effective price reference for highway vehicle transportation and is conducive to promoting the orderly development of the highway freight market.