Method and system for predicting scrapped vehicles

Abstract

The invention discloses a method and a system for predicting scrapped vehicles, which belong to the field of intelligent traffic big data. The method includes the following steps: extracting the characteristic information of vehicles from the track data of vehicles in a first preset time period; generating training samples according to the characteristic information of vehicles and a preset vehicle scrapping standard, and dividing the training samples into a training set and a testing set; training a prediction model according to the training set, and using the testing set to test the prediction model; and using the tested prediction model to predict scrapped vehicles in the future. In the invention, the prediction model is trained based on the historical track data of vehicles in a certain period, and the prediction model and the prediction result obtained finally are more scientific and reliable. Meanwhile, the operation rules of vehicles before scrapping are found out by combining the method with machine learning, and the problem of lagging in the prior art is solved. The vehicle manufacturers can also determine the marketing strategies more accurately.

Description

technical field [0001] The invention relates to the field of intelligent transportation big data, in particular to a method and system for predicting scrapped vehicles. Background technique [0002] With the rapid development of social economy, both private cars and logistics transport vehicles are growing at an exponential rate; various vehicle manufacturers are also constantly producing and selling vehicles of various brands, functions, and sizes . For vehicle manufacturers, knowing the needs of car buyers in a timely manner can make them produce more popular vehicles; at the same time, it is also important for vehicle manufacturers to be able to predict the scrapped vehicles on the market in a timely manner, so as to clarify marketing needs. equally important. However, the existing prediction methods for scrapped vehicles usually only consider the number of days that the vehicle has not been in operation, and use subjective experience to set the scrapping rules; At the...

AI Technical Summary

Problems solved by technology

However, the existing prediction methods for scrapped vehicles usually only consider the number of days that the vehicle has not been in operation, and use subjective experience to set the scrapping rules; At the same time, the use of subjective experience to set scrap rules also led to the prediction results being too subjective and not convincing, and there was a certain lag problem

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